CN113538255B - Motion fusion noise reduction method, device and computer readable storage medium - Google Patents
Motion fusion noise reduction method, device and computer readable storage medium Download PDFInfo
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Abstract
The invention discloses a motion fusion noise reduction method, a device and a computer readable storage medium, wherein the method comprises the following steps: acquiring a current visible light image and a current infrared light image of a target; performing time domain noise reduction on the current visible light image to obtain a current visible light noise reduction image, wherein the visible light time domain noise reduction intensity of a motion area of the current visible light image is smaller than that of a static area of the current visible light image; and fusing the moving region image of the current infrared light image with the moving region image of the current visible light noise reduction image to obtain a current visible light fusion image of the corresponding moving region. By the method, the defect that the motion area of the current visible light image cannot effectively utilize the time domain information to supplement image details can be overcome, and the detail information of the motion area of the current visible light image is better.
Description
Technical Field
The present invention relates to the field of image processing, and in particular, to a motion fusion noise reduction method, apparatus, and computer readable storage medium.
Background
In a low-light scene, a visible light image presented by a common camera is often saturated with noise, and a noise reduction technology is required to reduce noise of the image so as to improve visual effect. In recent years, technology for guiding a visible light image to reduce noise by using an infrared light image is increasingly widely applied, but guiding the visible light image to reduce noise by using the infrared light image is a difficulty, and improper guiding cannot improve visual effect and may cause some anomalies. If the image is subjected to temporal noise reduction, the risk of tailing effect is reduced by reducing the temporal noise reduction intensity of the moving region, but the moving region noise is more obvious than that of the static region, so that the noise suppression performance of the moving region is poorer as a noise reduction result under the effect of temporal noise reduction.
Disclosure of Invention
The invention mainly solves the technical problem of providing a motion fusion noise reduction method, a motion fusion noise reduction device and a computer readable storage medium, which can make up the defect that the motion area of the current visible light image can not effectively utilize time domain information to supplement image details, so that the detail information of the motion area of the current visible light image is better.
In order to solve the technical problems, the invention adopts a technical scheme that: provided is a motion fusion noise reduction method, comprising: acquiring a current visible light image and a current infrared light image of a target; performing time domain noise reduction on the current visible light image to obtain a current visible light noise reduction image, wherein the visible light time domain noise reduction intensity of a motion area of the current visible light image is smaller than that of a static area of the current visible light image; and fusing the moving region image of the current infrared light image with the moving region image of the current visible light noise reduction image to obtain a current visible light fusion image of the corresponding moving region.
The method for performing time domain noise reduction on the current visible light image comprises the following steps of: and fusing the still region image of the current infrared light image with the still region image of the current visible light noise reduction image to obtain a current visible light fusion image of the corresponding still region.
The method for obtaining the current visible light fusion image of the corresponding motion area comprises the following steps of: acquiring a first guide intensity and a second guide intensity of a current infrared light image, wherein the first guide intensity is larger than the second guide intensity; the first guiding intensity is obtained from a first area image of the current infrared light image, the second guiding intensity is obtained from a second area image of the current infrared light image, and the signal-to-noise ratio of the first area image of the current infrared light image is higher than that of the second area image of the current infrared light image; weighting and fusing a moving region image of the current infrared light image and a moving image of the current visible light noise reduction image; weighting and fusing the still region image of the current infrared light image and the still region image of the current visible light noise reduction image; the weight of the moving area image of the current infrared light image is first fusion intensity, the weight of the still area image of the current infrared light image is second fusion intensity, the first fusion intensity and the second fusion intensity are calculated by using the first guide intensity and the second guide intensity respectively, and the first fusion intensity is larger than the second fusion intensity.
The method comprises the following steps before the moving area image of the current infrared light image and the moving area image of the current visible light noise reduction image are fused: and carrying out noise reduction processing on the current infrared light image, wherein the noise reduction processing comprises time domain noise reduction and/or space domain noise reduction.
The method comprises the following steps before the time domain noise reduction of the current visible light image: and performing spatial domain noise reduction on the current visible light image.
The method for performing time domain noise reduction on the current visible light image comprises the following steps of: and performing spatial domain noise reduction on the current visible light image.
The time domain noise reduction of the current visible light image comprises the following steps: acquiring a plurality of historical visible light noise reduction images of a target, wherein the historical visible light noise reduction images are obtained by performing noise reduction treatment on the historical visible light images; acquiring comprehensive visible light time domain noise reduction intensity by utilizing a plurality of historical visible light noise reduction images and a current visible light image; and carrying out time domain noise reduction on the current visible light image by combining the comprehensive visible light time domain noise reduction intensity and the time domain noise reduction algorithm.
The noise reduction processing of the historical visible light image comprises the following steps: sequentially performing time domain noise reduction and space domain noise reduction on the historical visible light image; or sequentially performing spatial domain noise reduction and time domain noise reduction on the historical visible light image.
The method for obtaining the comprehensive visible light time domain noise reduction intensity by utilizing the plurality of historical visible light noise reduction images and the current visible light image comprises the following steps:
Acquiring infrared light time domain noise reduction intensity of an infrared light image and initial visible light time domain noise reduction intensity of a current visible light image, wherein the infrared light time domain noise reduction intensity of the infrared light image comprises first infrared light time domain noise reduction intensity and second infrared light time domain noise reduction intensity, the first infrared light time domain noise reduction intensity is noise reduction intensity for performing time domain noise reduction processing on a first area image of the infrared light image, the second infrared light time domain noise reduction intensity is noise reduction intensity for performing time domain noise reduction processing on a second area image of the infrared light image, and the signal to noise ratio of the first area image of the infrared light image is higher than that of the second area image of the infrared light image; the initial visible light time domain noise reduction intensity of the current visible light image comprises a first initial visible light time domain noise reduction intensity and a second initial visible light time domain noise reduction intensity, wherein the first initial visible light time domain noise reduction intensity is the time domain noise reduction intensity of a first area image corresponding to the visible light image, and the second initial visible light time domain noise reduction intensity is the time domain noise reduction intensity of a second area image corresponding to the visible light image; weighting and fusing the first infrared light time domain noise reduction intensity and the first initial visible light time domain noise reduction intensity; the second infrared light time domain noise reduction intensity and the second initial visible light time domain noise reduction intensity are subjected to weighted fusion to obtain the comprehensive visible light time domain noise reduction intensity; the weight of the first infrared light time domain noise reduction intensity is the first guiding intensity, and the weight of the second infrared light time domain noise reduction intensity is the second guiding intensity; the first guiding intensity is obtained from a first area image of the current infrared light image, and the second guiding intensity is obtained from a second area image of the current infrared light image.
Acquiring the infrared light spatial noise reduction intensity of an infrared light image and the initial visible light spatial noise reduction intensity of a current visible light image, wherein the infrared light spatial noise reduction intensity of the infrared light image comprises a first infrared light spatial noise reduction intensity and a second infrared light spatial noise reduction intensity, the first infrared light spatial noise reduction intensity is noise reduction intensity for performing spatial noise reduction processing on a first area image of the infrared light image, the second infrared light spatial noise reduction intensity is noise reduction intensity for performing spatial noise reduction processing on a second area image of the infrared light image, and the signal to noise ratio of the first area image of the infrared light image is higher than that of the second area image of the infrared light image; the initial visible light spatial noise reduction intensity of the current visible light image comprises a first initial visible light spatial noise reduction intensity and a second initial visible light spatial noise reduction intensity, wherein the first initial visible light spatial noise reduction intensity is the spatial noise reduction intensity of a first area image corresponding to the visible light image, and the second initial visible light spatial noise reduction intensity is the spatial noise reduction intensity of a second area image corresponding to the visible light image; weighting and fusing the first infrared light spatial domain noise reduction intensity and the first initial visible light spatial domain noise reduction intensity; the second infrared light spatial domain noise reduction intensity and the second initial visible light spatial domain noise reduction intensity are subjected to weighted fusion to obtain the comprehensive visible light spatial domain noise reduction intensity; the weight of the first infrared light spatial noise reduction intensity is the first guiding intensity, and the weight of the second infrared light spatial noise reduction intensity is the second guiding intensity; the first guiding intensity is obtained from a first area image of the current infrared light image, and the second guiding intensity is obtained from a second area image of the current infrared light image; and performing spatial denoising on the current visible light image by combining the comprehensive visible light spatial denoising intensity and the spatial denoising algorithm.
The method comprises the steps of fusing a motion area image of a current infrared light image with a motion area image of a current visible light noise reduction image to obtain a current visible light fusion image of a corresponding motion area, and further comprises the following steps: and performing spatial domain noise reduction on the visible light noise reduction image.
In order to solve the technical problems, the invention adopts another technical scheme that: the motion fusion noise reduction device comprises a processor, wherein the processor is used for executing instructions to realize the motion fusion noise reduction method.
In order to solve the technical problems, the invention adopts another technical scheme that: there is provided a computer readable storage medium for storing instructions/program data executable to implement the above described motion fusion noise reduction method.
The beneficial effects of the invention are as follows: compared with the prior art, the method and the device have the advantages that after the current visible light image is subjected to spatial domain noise reduction, the moving region image of the current visible light noise reduction image is fused with the corresponding image of the moving region of the current infrared light image, so that the defect that the moving region of the current visible light image cannot effectively utilize time domain information to supplement image details is overcome, the detail information of the moving region of the current visible light image is better, and the visual impression is better.
Drawings
FIG. 1 is a schematic flow chart of a motion fusion noise reduction method according to an embodiment of the application;
FIG. 2 is a flow chart of another motion fusion noise reduction method in an embodiment of the application;
FIG. 3 is a flow chart of a method for fusing a current infrared light image and a current visible light noise reduction image in an embodiment of the present application;
FIG. 4 is a schematic flow chart of the noise reduction process for the current infrared light image in the embodiment of the application;
FIG. 5 is a schematic flow chart of the noise reduction processing of the current visible light image in the embodiment of the application;
FIG. 6 is a schematic diagram of a motion fusion noise reducer in an embodiment of the application;
FIG. 7 is a schematic diagram of a motion fusion noise reduction device in an embodiment of the application;
Fig. 8 is a schematic structural view of a computer-readable storage medium in an embodiment of the present application.
Detailed Description
In order to make the objects, technical solutions and effects of the present invention clearer and more specific, the present invention will be described in further detail below with reference to the accompanying drawings and examples.
Referring to fig. 1, fig. 1 is a flowchart of a motion fusion noise reduction method according to an embodiment of the application. It should be noted that, if there are substantially the same results, the present embodiment is not limited to the flow sequence shown in fig. 1. As shown in fig. 1, the present embodiment includes:
s110: a current visible light image and a current infrared light image of the target are acquired.
In this embodiment, a device that simultaneously captures a visible light image and an infrared light image may be used to simultaneously acquire a visible light image and an infrared light image of a target, such as a thermal infrared imager or the like. It is also possible to acquire a visible light image and an infrared light image of the object separately using different devices, such as a visible light camera and an infrared camera, respectively. When different devices are used for acquiring the visible light image and the infrared light image, the two devices can be placed at the same position, and the optical axes of the lenses are in the same direction and parallel to acquire the visible light image and the infrared light image at the same angle. The two devices may also be placed in different locations to acquire visible and infrared images at different angles. This embodiment is not limited to the apparatus used and the image acquisition angle. The visible light image of the current frame to be processed is taken as a current visible light image, and the infrared light image corresponding to the current visible light is taken as a current infrared light image.
S130: and performing time domain noise reduction on the current visible light image to obtain a current visible light noise reduction image.
The image may be divided into a moving area and a still area according to the difference of the motion information, and in the embodiment of the present application, the moving area and the still area may be divided according to the motion information detection method, and the moving area and the still area may be considered to be defined, which is not limited herein. The information change of the moving area is larger than that of the static area between the adjacent frame images, so that different time domain noise reduction intensities are set in the moving area and the static area of the current visible light image to reduce the influence of the tailing effect on image noise reduction, and the time domain noise reduction is carried out on the current visible light image to obtain the current visible light noise reduction image. The visible light time domain noise reduction intensity of the moving region of the current visible light image is smaller than that of the static region of the current visible light image.
S150: and fusing the motion area of the current infrared light image with the motion area of the current visible light noise reduction image to obtain a current visible light fusion image of the corresponding motion area.
And introducing information of a motion region of the current infrared light image into the motion region of the current visible light noise reduction image, and fusing the motion region of the current infrared light image with the motion region of the current visible light noise reduction image to obtain a current visible light fused image of the corresponding motion region.
In this embodiment, after spatial domain noise reduction is performed on the current visible light image, the moving region image of the current visible light noise reduction image is fused with the image of the moving region of the corresponding current infrared light image, so that the defect that the moving region of the current visible light image cannot effectively utilize time domain information to supplement image details is overcome, the detail information of the moving region of the current visible light image is better, and the visual impression is better.
Referring to fig. 2, fig. 2 is a schematic flow chart of another motion fusion noise reduction method according to an embodiment of the application. It should be noted that, if there are substantially the same results, the embodiment is not limited to the flow sequence shown in fig. 2. As shown in fig. 2, the present embodiment includes:
S210: a current visible light image and a current infrared light image of the target are acquired.
S230: and performing time domain noise reduction on the current visible light image to obtain a current visible light noise reduction image.
S250: fusing the moving region image of the current infrared light image with the moving region image of the current visible light noise reduction image to obtain a current visible light fusion image of the corresponding moving region; and fusing the current infrared light image of the static area with the current visible light noise reduction image of the static area to obtain a current visible light fusion image of the corresponding static area.
And introducing information of the moving region of the current infrared light image into the moving region of the current visible light noise reduction image, and introducing information of the still region of the current infrared light image into the still region of the current visible light noise reduction image.
When the current infrared light image and the current visible light noise reduction image are fused, an original current visible light image which is not subjected to noise reduction treatment can be used, the current infrared light image which is subjected to noise reduction treatment can also be used, and the noise reduction method can be spatial domain noise reduction, temporal domain noise reduction, combination of spatial domain noise reduction and temporal domain noise reduction or other noise reduction methods, and is not limited.
S270: and performing spatial domain noise reduction on the current visible light fusion image.
After the whole current infrared light image and the current visible light image are fused, the current visible light fusion image is subjected to sequential spatial domain noise reduction treatment, and the specific noise reduction method is not limited.
Referring to fig. 3, fig. 3 is a flow chart of a method for fusing a current infrared light image and a current visible light noise reduction image in an embodiment of the application. It should be noted that, if there are substantially the same results, the embodiment is not limited to the flow sequence shown in fig. 3. As shown in fig. 3, the present embodiment includes:
S310: and acquiring a first guiding intensity and a second guiding intensity of the current infrared light image.
The important index for measuring the quality of an image when the signal to noise ratio of the image refers to the ratio of the size of a video signal to the size of a noise wave signal, the noise is small in an image area with high signal to noise ratio, and the noise is large in an image area with low signal to noise ratio. Different areas of the current infrared light image have different signal-to-noise ratios, different guide intensities are set according to the different signal-to-noise ratios, larger guide intensity is set in areas with high signal-to-noise ratios, and smaller guide intensity is set in areas with low signal-to-noise ratios. Alternatively, the entire infrared light may be set to the same guiding intensity, or guiding intensities of different gradient magnitudes may be set according to the signal-to-noise gradient.
And dividing the current infrared light image into a first area and a second area according to different signal-to-noise ratios, wherein the signal-to-noise ratio of the current infrared light image in the first area is higher than that of the current infrared light image in the second area. The first guiding intensity of the first area image is increased as a whole, and the second guiding intensity of the second area image is decreased as a whole. In the embodiment of the application, the first area and the second area can be determined according to the brightness information, the chromaticity information and the like of the current infrared light image.
In one embodiment, the first region and the second region are determined based on luminance information of the current infrared light image. The method comprises the steps of presetting a first threshold value th1, a second threshold value th2 and a third threshold value th3, taking an area with a brightness value larger than th1 in a current infrared light image as a potential overexposure area, taking an area with a brightness value smaller than th2 in the current infrared light image as a potential information loss area, and taking other areas as normal areas. And calculating variance information of the overexposed region and the information lost region, wherein the variance information can be the variance information of each pixel point or the variance information of a plurality of pixel regions, if the variance information is higher than a third threshold th3, the variance information indicates that the brightness of the region image is too high or too low and is caused by material reflection characteristics, the variance information belongs to normal, otherwise, the region is indicated to be an information abnormal region. The normal area is defined as a first area, the information abnormal area is defined as a second area, the first area is provided with a first guidance intensity, the second area is provided with a second guidance intensity, and the guidance intensity can be considered to be set or calculated according to other information, and is not limited herein.
The first threshold th1, the second threshold th2, and the third threshold th3 are preset thresholds, and the default value needs to be determined according to the actual situation, in a specific embodiment, the first threshold th1 is 240, the second threshold th2 is 10, the third threshold th3 is 5, the calculated guiding strength is gui _ratio, and the guiding strength has a value range greater than or equal to 0 and less than or equal to 1.
In another embodiment, the guiding intensity may be set according to luminance information and chromaticity information of the current infrared light image subjected to the noise reduction process; the guiding intensity can be calculated by combining the current infrared light image which is not subjected to noise reduction treatment and the current infrared light image which is subjected to noise reduction treatment; the guidance intensity may also be calculated jointly in connection with the current visible light image and the current infrared light image.
S330: and carrying out weighted fusion on the current infrared light image and the current visible light noise reduction image by using the first guide intensity and the second guide intensity.
In this embodiment, the current infrared light image that is weighted and fused with the current visible light noise reduction image may be the initial current infrared light image or the image after the noise reduction process. The current infrared light image may be noise reduced by using the noise reduction method described above, which is not described herein.
According to the motion information of the current visible light image and the current infrared light image, different initial fusion intensities are set for the areas with different motion information, and the initial fusion intensity of the motion area is larger than that of the static area. The range of values of the initial fusion strength is greater than or equal to 0 and less than or equal to 1. In one embodiment, a greater initial first fusion intensity is set in the motion zone with a value biased toward 1 and a smaller initial second fusion intensity is set in the stationary zone with a value biased toward 0.
The initial fusion intensity is adjusted according to the guiding intensity. First, the fourth preset threshold th4 is multiplied by the guiding intensity to obtain the adjusted guiding intensity, the adjusted guiding intensity is gui _th, the value from the guiding intensity after adjustment to the guiding intensity greater than 1 is 1, the value from the guiding intensity after adjustment to the guiding intensity less than 0 is 0, and the value range of the guiding intensity is kept to be greater than or equal to 0 and less than or equal to 1. The guiding intensity of the corresponding pixel point is multiplied by the initial fusion intensity to obtain the adjusted fusion intensity, which is fusion_ratio. The fourth threshold th4 is a predetermined threshold, and optionally, the default value of the fourth threshold th4 is 1. After adjustment, the fusion strength of the motion region is the first fusion strength, the fusion strength of the static region is the second fusion strength, and the first fusion strength is greater than the second fusion strength.
And the current infrared light image and the current visible light noise reduction image are fused by utilizing the adjusted fusion intensity, so that various fusion modes can be used. In one embodiment, a motion area image of a current infrared light image and a motion area image of a current visible light noise reduction image are subjected to weighted fusion, and the weight of the motion area image of the current infrared light image is a first fusion intensity; and carrying out weighted fusion on the still region image of the current infrared light image and the still region image of the current visible light noise reduction image, wherein the weight of the still region image of the current infrared light image is the second fusion intensity, and obtaining the current visible light fusion image. The current visible light noise reduction image is divided into a current visible light brightness channel noise reduction image and a current visible light color channel noise reduction image. The current visible light brightness channel noise reduction image and the current visible light color brightness channel noise reduction image are respectively fused with the current infrared light image in the same fusion mode, and in this embodiment, the current visible light brightness channel noise reduction image and the current infrared light image are fused for illustration. The specific fusion formula is as follows:
vis_0＝(1-fusion_ratio)×vis+fusion_ratio×nir
Wherein vis is the current visible light brightness channel noise reduction image, nir is the current infrared light image, and vis_0 is the current visible light fusion image.
In this embodiment, different guiding intensities are set according to different signal-to-noise ratios of each region of the current infrared light image, different fusion intensities are set according to different motion information of the current visible light image and the motion region and the static region of the current infrared light image, then the fusion intensities are adjusted by using the guiding intensities, more information of the current infrared light image is fused in the motion region of the current visible light noise reduction image, less information of the current infrared light image is fused in the static region, more detailed information can be supplemented in the motion region, visual impression is better, and the information before the fusion intensity can be fully utilized in the static region is reduced, so that the fidelity of brightness information is ensured.
In the embodiment of the application, the current infrared light image to be subjected to image fusion can be an image subjected to noise reduction processing, and the noise reduction method comprises spatial noise reduction, temporal noise reduction, combination of spatial noise reduction and temporal noise reduction or other noise reduction methods. Referring to fig. 4, fig. 4 is a schematic flow chart of a noise reduction process for a current infrared light image according to an embodiment of the application. It should be noted that, if there are substantially the same results, the embodiment is not limited to the flow sequence shown in fig. 4. As shown in fig. 4, the present embodiment includes:
S410: and performing motion detection on the current infrared light image to obtain the motion information of the current infrared light image.
The motion detection of the current infrared light image can be performed by using a plurality of motion detection methods, such as a frame difference method, an optical flow method, a background difference method and the like, so as to obtain the motion information of the current infrared light image. In one embodiment, the frame difference method is used to detect motion of the current infrared light image, and compare the two front and rear frames of infrared light images, if the difference between the pixels of the two front and rear frames of images of a region is large, the region is more biased to the motion region, and if the difference between the pixels of the two front and rear frames of images of a region is small, the region is more biased to the still region. In another embodiment, the current infrared light image is subjected to motion detection by using an optical flow method, if the optical flow value of a region is large, the region is more likely to be a moving region, and if the optical flow value of a region is small, the region is more likely to be a static region.
S430: and performing spatial domain noise reduction on the current infrared light image.
The spatial domain noise reduction intensity of the current infrared light image can be obtained according to various image information of the current infrared light image. In an embodiment, the current infrared light image spatial noise reduction intensity can be determined by using image information such as variance and edge, when the variance information of an area image is larger, the noise of the area image is larger, so that the larger current infrared light image spatial noise reduction intensity is set in the area to reduce the noise of the area when the spatial noise reduction is carried out subsequently; when the edge information of an area image is stronger, setting smaller current infrared light image spatial domain noise reduction intensity in the area so as to keep the large edge information of the area when spatial domain noise reduction is carried out later.
And adjusting the spatial domain noise reduction intensity of the obtained current infrared light image according to the motion information of the current infrared light image. According to different motion information, the spatial noise reduction intensity of the current infrared light image is differentiated, if the current infrared light image comprises an area A and an area B, the spatial noise reduction intensity of the front infrared light image of the area A is determined to be the same as that of the front infrared light image of the area B by utilizing variance information, but the area A is a motion area, the area B is a static area, the spatial noise reduction intensity of the front infrared light image of the area A is properly increased, the spatial noise reduction intensity of the front infrared light image of the area B is reduced, and the adjusted spatial noise reduction intensity of the current infrared light image is nirspa _ratio.
And according to the adjusted spatial noise reduction intensity of the current infrared light image, the current infrared light image is noise reduced by using a spatial noise reduction algorithm, and the specific spatial noise reduction algorithm is not limited herein.
S450: and performing time domain noise reduction on the current infrared light image.
The method comprises the steps of obtaining a plurality of historical infrared noise reduction images of a target, wherein the historical infrared noise reduction images are obtained by performing noise reduction processing on the historical infrared images. In one embodiment, a temporal noise reduction image of the plurality of forward frame images is obtained, and the temporal noise reduction intensity of the current infrared image is determined by combining the current infrared image and the plurality of historical infrared noise reduction images.
And adjusting the time domain noise reduction intensity of the obtained current infrared light image according to the motion information of the current infrared light image. According to different motion information, the time domain noise reduction intensity of the current infrared light image of the motion area is reduced, even the time domain noise reduction intensity of the current infrared light image of the motion area can be set to zero, and the time domain noise reduction intensity of the current infrared light image of the static area is increased. In one embodiment, for the motion region, the inverse of the motion information of the current infrared light image is taken as the temporal noise reduction intensity of the current infrared light image. The adjusted time domain noise reduction intensity of the current infrared light image is nirtim _ratio.
And according to the adjusted time domain noise reduction intensity of the current infrared light image, the current infrared light image is subjected to noise reduction by using a time domain noise reduction algorithm, and the specific time domain noise reduction algorithm is not limited herein.
Wherein, only one of the steps S410 and S430 may be performed, or both steps S410 and S430 may be continuously performed. The specific order of S410 and S430 is not limited, and if spatial domain noise reduction of S410 is performed first, temporal domain noise reduction is performed on the current infrared spatial domain noise reduction image after spatial domain noise reduction in S430; if the temporal denoising of S430 is performed first, spatial domain denoising is performed on the current infrared temporal denoising image after temporal denoising at S410.
S470: and carrying out optimization treatment on the current infrared light image to obtain the current infrared light image after noise reduction.
And carrying out post-processing operation on the current infrared light image, namely carrying out spatial domain noise reduction on the current infrared light image again to obtain a current infrared light noise reduction image. The specific airborne noise reduction method is the same as S410, and will not be described here again.
In the embodiment, the current infrared light image is firstly subjected to space domain and time domain noise reduction, and the output part of the time domain noise reduction is also used as the historical infrared light image input in the next frame of time domain noise reduction, so that the detail information after the time domain noise reduction can be ensured not to be lost in the next frame of image in the time domain noise reduction. And then, performing space domain noise reduction again on the basis of the noise reduction result, and reducing the requirements on the prior space domain and time domain noise reduction strength while optimizing the noise reduction effect of the final infrared light image. By the method, the visual effect and the appearance of the finally presented current infrared light noise reduction image are better.
In the embodiment of the application, the current visible light image to be subjected to image fusion can be an image subjected to time domain noise reduction processing only, or can be an image subjected to spatial domain noise reduction and time domain noise reduction processing. Referring to fig. 5, fig. 5 is a schematic flow chart of a noise reduction process for a current visible light image according to an embodiment of the application. It should be noted that, if there are substantially the same results, the embodiment is not limited to the flow sequence shown in fig. 5. As shown in fig. 5, the present embodiment includes:
s510: and performing motion detection on the current visible light image to obtain the motion information of the current visible light image.
The current visible light image can be divided into a current visible light brightness channel image and a current visible light color channel image, the current visible light brightness channel image and the current visible light color channel image are respectively subjected to motion detection, and motion detection methods such as a frame difference method, an optical flow method, a background difference method and the like can be used for detection to obtain motion information of the current visible light brightness channel image and the current visible light color channel image. The specific acquisition method is the same as that of the current infrared light image motion information acquired in S410, and will not be described here again.
S530: and performing spatial domain noise reduction on the current visible light image.
The current visible light image spatial domain noise reduction intensity can be obtained according to various image information of the current visible light image, and then the obtained current visible light spatial domain noise reduction intensity is adjusted according to the motion information of the current visible light image. The specific acquiring method is the same as that of the current infrared light image after the step S430 is acquired and the spatial noise reduction strength is not described herein.
And carrying out second adjustment on the current visible airspace noise reduction intensity by using the guide intensity. The method comprises the steps of presetting a fifth threshold th5 and a sixth threshold th6, taking a first guiding intensity or a product of the fifth threshold th5 and the first guiding intensity as a first weight, taking a second guiding intensity or a product of the sixth threshold th6 and the second guiding intensity as a second weight, re-taking a value larger than 1 of the first weight and the second weight as 1, and re-taking a value smaller than 0 as 0, so that the initial visible light spatial domain noise reduction intensity is obtained. Wherein the obtained first weight is nor_th, and the obtained second weight is unnor _th.
Taking the current infrared light spatial noise reduction intensity of the first region of the current infrared light image as the first current infrared light spatial noise reduction intensity, and taking the initial visible light spatial noise reduction intensity of the corresponding region of the current visible light image as the first initial visible light spatial noise reduction intensity; taking the current infrared light spatial noise reduction intensity of the second region of the current infrared light image as the second infrared light spatial noise reduction intensity, and taking the initial visible light spatial noise reduction intensity of the corresponding region of the current visible light image as the second initial visible light spatial noise reduction intensity. Carrying out weighted fusion on the first infrared light spatial noise reduction intensity and the first initial visible light spatial noise reduction intensity, wherein the fusion weight of the first infrared light spatial noise reduction intensity is a first weight; and carrying out weighted fusion on the second infrared light spatial noise reduction intensity and the second initial visible light spatial noise reduction intensity, wherein the fusion weight of the second infrared light spatial noise reduction intensity is a second weight, and obtaining the comprehensive visible light spatial noise reduction intensity.
The current visible light noise reduction image is divided into a current visible light brightness channel noise reduction image and a current visible light color channel noise reduction image. The current visible light brightness channel image and the current visible light color brightness channel image of the current visible light image are respectively subjected to spatial domain noise reduction, and the following embodiment takes the spatial domain noise reduction of the current visible light brightness channel image as an example. The specific fusion formula is as follows:
Wherein visspa _ratio is the spatial noise reduction intensity of the current visible light brightness channel noise reduction image, nirspa _ratio is the spatial noise reduction intensity of the current infrared light image, and visspa _ratio_0 is the spatial noise reduction intensity of the current visible light image.
And according to the adjusted spatial noise reduction intensity of the current visible light image, the current visible light image is noise reduced by using a spatial noise reduction algorithm, and the specific spatial noise reduction algorithm is not limited herein.
S550: and performing time domain noise reduction on the current visible light image.
And acquiring a plurality of historical visible light noise reduction images of the target, wherein the historical visible light noise reduction images are obtained by performing noise reduction processing on the historical visible light images. In an embodiment, a plurality of visible light noise reduction images of forward frame images, which are sequentially subjected to spatial domain noise reduction and temporal domain noise reduction, are obtained, and the current visible light image and a plurality of historical visible light noise reduction images are combined to determine the temporal domain noise reduction intensity of the initial visible light image. In another embodiment, a plurality of visible light noise reduction images of forward frame images, which are sequentially subjected to time domain noise reduction and space domain noise reduction, are obtained, and the time domain noise reduction intensity of the initial visible light image is determined by combining the current visible light image and the plurality of historical visible light noise reduction images.
The time domain noise reduction intensity of the current visible light image can be obtained according to various image information of the current visible light image, and then the obtained time domain noise reduction intensity of the current visible light image is adjusted according to the motion information of the current visible light image. The specific acquisition method is the same as the time domain noise reduction strength of the current infrared light image after the adjustment in S450, and will not be described here again.
And carrying out second adjustment on the current visible time domain noise reduction intensity by utilizing the guide intensity. The method comprises the steps of presetting a seventh threshold th7 and an eighth threshold th8, taking the first guiding intensity or the product of the seventh threshold th7 and the first guiding intensity as a third weight, taking the product of the second guiding intensity or the eighth threshold th8 and the second guiding intensity as a fourth weight, re-taking the value larger than 1 in the third weight and the fourth weight as 1, and re-taking the value smaller than 0 as 0, so as to obtain the initial visible light time domain noise reduction intensity. Wherein the third weight is nor_th1 and the fourth weight is unnor _th1.
Taking the current infrared light time domain noise reduction intensity of the first region of the current infrared light image as the first current infrared light time domain noise reduction intensity, and taking the initial visible light time domain noise reduction intensity of the corresponding region of the current visible light image as the first initial visible light time domain noise reduction intensity; taking the current infrared light time domain noise reduction intensity of the second region of the current infrared light image as the second infrared light time domain noise reduction intensity, and taking the initial visible light time domain noise reduction intensity of the corresponding region of the current visible light image as the second initial visible light time domain noise reduction intensity. Carrying out weighted fusion on the first infrared light time domain noise reduction intensity and the first initial visible light time domain noise reduction intensity, wherein the fusion weight of the first infrared light time domain noise reduction intensity is a first weight; and carrying out weighted fusion on the second infrared light time domain noise reduction intensity and the second initial visible light time domain noise reduction intensity, wherein the fusion weight of the second infrared light time domain noise reduction intensity is a second weight, and obtaining the comprehensive visible light time domain noise reduction intensity.
The current visible light noise reduction image is divided into a current visible light brightness channel noise reduction image and a current visible light color channel noise reduction image. The current visible light brightness channel image and the current visible light color brightness channel image of the current visible light image are respectively subjected to time domain noise reduction, and the following embodiments take the time domain noise reduction of the current visible light brightness channel image as an example. The specific fusion formula is as follows:
Wherein visspa _ratio_1 is the temporal noise reduction intensity of the current visible light luminance channel noise reduction image, nirspa _ratio_1 is the current infrared light image temporal noise reduction intensity, and visspa _ratio_1 is the current visible light image temporal noise reduction intensity.
And according to the adjusted time domain noise reduction intensity of the current visible light image, the current visible light image is noise reduced by using a time domain noise reduction algorithm, and the specific time domain noise reduction algorithm is not limited herein.
In this embodiment, the quality of the infrared light image can be discriminated by setting different guide intensities according to the signal-to-noise ratio of each region of the current infrared light image. And carrying out different spatial domain noise reduction and time domain noise reduction on different areas of the current infrared light image by utilizing different guide intensities. After the time domain noise reduction and the space domain noise reduction are performed once, the space domain noise reduction is performed once again, so that the requirements on the prior time domain noise reduction and the prior space domain noise reduction are reduced, and the visual effect of the final image is better. Meanwhile, different fusion intensities are set according to different motion information of a current visible light image and motion information of a current infrared light image motion area and motion information of a static area, then the fusion intensity is adjusted by using guide intensity, more information of the current infrared light image is fused in the motion area of the current visible light noise reduction image, less information of the current infrared light image is fused in the static area, more detail information can be supplemented in the motion area, visual impression is better, and the information before the fusion intensity can be fully utilized in the static area is reduced, so that the fidelity of brightness information is ensured.
Referring to fig. 6, fig. 6 is a schematic structural diagram of a motion fusion noise reduction device according to an embodiment of the application. In this embodiment, the motion fusion noise reduction device includes an acquisition module 61, a noise reduction module 62, and a fusion module 63.
Wherein the acquisition module 61 is configured to acquire a current visible light image and a current infrared light image of the target; the noise reduction module 62 is configured to perform time domain noise reduction on the current visible light image to obtain a current visible light noise reduction image; the fusion module 63 is configured to fuse a motion region of a current infrared light image with a motion region of a current visible light noise reduction image, so as to obtain a current visible light fusion image corresponding to the motion region.
In this embodiment, after spatial domain noise reduction is performed on the current visible light image, the moving region image of the current visible light noise reduction image is fused with the image of the moving region of the corresponding current infrared light image, so that the defect that the moving region of the current visible light image cannot effectively utilize time domain information to supplement image details is overcome, the detail information of the moving region of the current visible light image is better, and the visual impression is better.
Referring to fig. 7, fig. 7 is a schematic structural diagram of a motion fusion noise reduction device according to an embodiment of the application. In this embodiment, the motion fusion noise reduction device 71 comprises a processor 72.
The processor 72 may also be referred to as a CPU (Central Processing Unit ). The processor 72 may be an integrated circuit chip having signal processing capabilities. Processor 72 may also be a general purpose processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other programmable logic device, discrete gate or transistor logic, discrete hardware components. The general purpose processor may be a microprocessor or the processor 72 may be any conventional processor or the like.
The motion fusion noise reduction device 71 may further comprise a memory (not shown) for storing instructions and data required for the operation of the processor 72.
The processor 72 is operative to execute instructions to implement the methods provided by any of the embodiments of the motion fusion noise reduction method of the present application and any non-conflicting combinations described above.
Referring to fig. 8, fig. 8 is a schematic diagram of a computer readable storage medium according to an embodiment of the application. The computer readable storage medium 81 of an embodiment of the present application stores instruction/program data 82 that when executed implement the method provided by any embodiment of the motion fusion noise reduction method of the present application, as well as any non-conflicting combination. Wherein the instructions/program data 82 may be stored in the storage medium 81 as a software product to cause a computer device (which may be a personal computer, a server, or a network device, etc.) or a processor (processor) to perform all or part of the steps of the methods of the embodiments of the application. And the aforementioned storage medium 81 includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk, an optical disk, or other various media capable of storing program codes, or a terminal device such as a computer, a server, a mobile phone, a tablet, or the like.
In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices, and methods may be implemented in other manners. For example, the apparatus embodiments described above are merely illustrative, e.g., the division of elements is merely a logical functional division, and there may be additional divisions of actual implementation, e.g., multiple elements or components may be combined or integrated into another system, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be an indirect coupling or communication connection via some interfaces, devices or units, which may be in electrical, mechanical or other form.
In addition, each functional unit in the embodiments of the present application may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.
The foregoing description is only of embodiments of the present application, and is not intended to limit the scope of the application, and all equivalent structures or equivalent processes using the descriptions and the drawings of the present application or directly or indirectly applied to other related technical fields are included in the scope of the present application.
Claims (12)
1. A method of motion fusion noise reduction, the method comprising:
Acquiring a current visible light image and a current infrared light image of a target;
Performing time domain noise reduction on the current visible light image to obtain a current visible light noise reduction image, wherein the visible light time domain noise reduction intensity of a motion area of the current visible light image is smaller than that of a static area of the current visible light image; the time domain noise reduction of the current visible light image includes:
Acquiring a plurality of historical visible light noise reduction images of the target, wherein the historical visible light noise reduction images are obtained by performing noise reduction processing on the historical visible light images;
Acquiring comprehensive visible light time domain noise reduction intensity by utilizing the plurality of historical visible light noise reduction images and the current visible light image;
Performing time domain noise reduction on the current visible light image by combining the comprehensive visible light time domain noise reduction intensity and a time domain noise reduction algorithm;
And fusing the moving region image of the current infrared light image with the moving region image of the current visible light noise reduction image to obtain a current visible light fusion image of the corresponding moving region.
2. The method of motion fusion noise reduction according to claim 1, wherein the temporally denoising the current visible light image comprises:
And fusing the still region image of the current infrared light image with the still region image of the current visible light noise reduction image to obtain a current visible light fusion image of the corresponding still region.
3. The method of motion fusion noise reduction according to claim 2, wherein the fusing the motion area image of the current infrared light image and the motion area image of the current visible light noise reduction image to obtain a current visible light fusion image of a corresponding motion area comprises:
Acquiring a first guide intensity and a second guide intensity of the current infrared light image, wherein the first guide intensity is larger than the second guide intensity; the first guiding intensity is obtained from a first area image of the current infrared light image, the second guiding intensity is obtained from a second area image of the current infrared light image, and the signal to noise ratio of the first area image of the current infrared light image is higher than that of the second area image of the current infrared light image;
weighting and fusing the motion area image of the current infrared light image and the motion image of the current visible light noise reduction image; weighting and fusing the still region image of the current infrared light image and the still region image of the current visible light noise reduction image;
The weight of the moving area image of the current infrared light image is first fusion intensity, the weight of the static area image of the current infrared light image is second fusion intensity, the first fusion intensity and the second fusion intensity are calculated by the aid of the first guide intensity and the second guide intensity respectively, and the first fusion intensity is larger than the second fusion intensity.
4. A method of motion fusion noise reduction according to claim 3, wherein the fusing of the motion zone image of the current infrared light image with the motion zone image of the current visible light noise reduction image comprises:
and carrying out noise reduction processing on the current infrared light image, wherein the noise reduction processing comprises time domain noise reduction and/or space domain noise reduction.
5. The method of motion fusion noise reduction according to claim 1, wherein prior to temporal noise reduction of the current visible light image comprises:
and performing spatial domain noise reduction on the current visible light image.
6. The method of motion fusion noise reduction according to claim 1, wherein the temporally denoising the current visible light image comprises:
and performing spatial domain noise reduction on the current visible light image.
7. The motion fusion noise reduction method according to claim 1, wherein the noise reduction processing of the history visible light image includes:
Sequentially performing time domain noise reduction processing and space domain noise reduction processing on the historical visible light image; or (b)
And sequentially performing spatial domain noise reduction and time domain noise reduction on the historical visible light image.
8. The method of motion fusion noise reduction according to claim 1, wherein the obtaining the integrated visible light temporal noise reduction intensity using the plurality of historical visible light noise reduction images and the current visible light image comprises:
Acquiring infrared light time domain noise reduction intensity of the infrared light image and initial visible light time domain noise reduction intensity of the current visible light image, wherein the infrared light time domain noise reduction intensity of the infrared light image comprises first infrared light time domain noise reduction intensity and second infrared light time domain noise reduction intensity, the first infrared light time domain noise reduction intensity is noise reduction intensity for performing time domain noise reduction processing on a first area image of the infrared light image, the second infrared light time domain noise reduction intensity is noise reduction intensity for performing time domain noise reduction processing on a second area image of the infrared light image, and the signal to noise ratio of the first area image of the infrared light image is higher than that of the second area image of the infrared light image; the initial visible light time domain noise reduction intensity of the current visible light image comprises a first initial visible light time domain noise reduction intensity and a second initial visible light time domain noise reduction intensity, wherein the first initial visible light time domain noise reduction intensity is the time domain noise reduction intensity of a first area image corresponding to the visible light image, and the second initial visible light time domain noise reduction intensity is the time domain noise reduction intensity of a second area image corresponding to the visible light image;
Weighting and fusing the first infrared light time domain noise reduction intensity and the first initial visible light time domain noise reduction intensity; the second infrared light time domain noise reduction intensity and the second initial visible light time domain noise reduction intensity are subjected to weighted fusion to obtain the comprehensive visible light time domain noise reduction intensity; the weight of the first infrared light time domain noise reduction intensity is first guide intensity, and the weight of the second infrared light time domain noise reduction intensity is second guide intensity;
The first guiding intensity is obtained from a first area image of the current infrared light image, and the second guiding intensity is obtained from a second area image of the current infrared light image.
9. The motion fusion noise reduction method according to claim 5 or 6, wherein spatially reducing the current visible light image comprises:
Acquiring the infrared light spatial noise reduction intensity of the infrared light image and the initial visible light spatial noise reduction intensity of the current visible light image, wherein the infrared light spatial noise reduction intensity of the infrared light image comprises a first infrared light spatial noise reduction intensity and a second infrared light spatial noise reduction intensity, the first infrared light spatial noise reduction intensity is noise reduction intensity for performing spatial noise reduction processing on a first area image of the infrared light image, the second infrared light spatial noise reduction intensity is noise reduction intensity for performing spatial noise reduction processing on a second area image of the infrared light image, and the signal to noise ratio of the first area image of the infrared light image is higher than that of the second area image of the infrared light image; the initial visible light spatial noise reduction intensity of the current visible light image comprises a first initial visible light spatial noise reduction intensity and a second initial visible light spatial noise reduction intensity, wherein the first initial visible light spatial noise reduction intensity is the spatial noise reduction intensity of a first area image corresponding to the visible light image, and the second initial visible light spatial noise reduction intensity is the spatial noise reduction intensity of a second area image corresponding to the visible light image;
weighting and fusing the first infrared light spatial domain noise reduction intensity and the first initial visible light spatial domain noise reduction intensity; the second infrared light spatial domain noise reduction intensity and the second initial visible light spatial domain noise reduction intensity are subjected to weighted fusion to obtain the comprehensive visible light spatial domain noise reduction intensity; the weight of the first infrared light spatial noise reduction intensity is first guiding intensity, and the weight of the second infrared light spatial noise reduction intensity is second guiding intensity;
The first guiding intensity is obtained from a first area image of the current infrared light image, and the second guiding intensity is obtained from a second area image of the current infrared light image;
And performing spatial denoising on the current visible light image by combining the comprehensive visible light spatial denoising intensity and the spatial denoising algorithm.
10. The method for motion fusion noise reduction according to claim 1, wherein the fusing the motion area image of the current infrared light image and the motion area of the current visible light noise reduction image to obtain a current visible light fusion image of a corresponding motion area further comprises:
And performing spatial domain noise reduction on the visible light noise reduction image.
11. A motion fusion noise reduction device comprising a processor for executing instructions to implement the motion fusion noise reduction method of any of claims 1-10.
12. A computer readable storage medium storing instructions/program data executable to implement the motion fusion noise reduction method of any one of claims 1-10.
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