CN114066794A - Image processing method, device and equipment and storage medium - Google Patents
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Abstract
The embodiment of the application provides an image processing method, an image processing device, image processing equipment and a computer storage medium, wherein the method comprises the following steps: acquiring an image to be processed; carrying out contrast enhancement processing on the image to be processed to obtain a global enhanced image; determining a target local image of the image to be processed, and performing contrast enhancement processing on the target local image to obtain a local enhanced image; and fusing the local enhanced image and the global enhanced image to enable the local enhanced image to replace the position of the target local image in the global enhanced image, so as to obtain the local enhanced global image of the image to be processed.
Description
Technical Field
The present application relates to the field of image processing technologies, and in particular, to an image processing method, an image processing apparatus, and a computer-readable storage medium.
Background
At present, the infrared imaging technology is gradually expanded from the application in the initial military field to the civil fields of medical diagnosis, crop monitoring, forest fire prevention early warning, mineral resource exploration and the like due to the characteristics of strong anti-interference capability, all-weather work and the like. In these particular applications, the quality of the image is critical to the ability of infrared technology to function.
However, the infrared detector is easily affected by atmospheric radiation and noise, so the detected infrared image usually has the defects of low contrast and the like, the visual effect is not good, and the infrared detector cannot be directly applied to the high-precision imaging field. In order to improve the visual effect of the infrared image and make the infrared image clearer, it is necessary to enhance the contrast of the infrared image to improve its signal-to-noise ratio, and current image enhancement algorithms usually process the whole scene image, and the local target concerned in the image may still not be clearly represented because of the smaller occupation ratio.
Disclosure of Invention
In order to solve the existing technical problems, the present application provides an image processing method, an apparatus and a device, and a computer readable storage medium capable of effectively highlighting a local area while maintaining global image contrast.
In order to achieve the above purpose, the technical solution of the embodiment of the present application is implemented as follows:
in a first aspect, an embodiment of the present application provides an image processing method, which is applied to an image processing apparatus, and includes:
acquiring an image to be processed;
carrying out contrast enhancement processing on the image to be processed to obtain a global enhanced image;
determining a target local image of the image to be processed, and performing contrast enhancement processing on the target local image to obtain a local enhanced image;
and fusing the local enhanced image and the global enhanced image to enable the local enhanced image to replace the position of the target local image in the global enhanced image, so as to obtain the local enhanced global image of the image to be processed.
In a second aspect, an embodiment of the present application provides an image processing apparatus, including:
the acquisition module is used for acquiring an image to be processed;
the first enhancement processing module is used for carrying out contrast enhancement processing on the image to be processed to obtain a global enhanced image;
the second enhancement processing module is used for determining a target local image of the image to be processed and carrying out contrast enhancement processing on the target local image to obtain a local enhanced image;
and the fusion module is used for fusing the local enhanced image and the global enhanced image to enable the local enhanced image to replace the position of the target local image in the global enhanced image so as to obtain the local enhanced global image of the image to be processed.
In a third aspect, an embodiment of the present application provides an image processing apparatus, including a processor, a memory connected to the processor, and a computer program stored on the memory and executable by the processor, where the computer program, when executed by the processor, implements the image processing method according to any embodiment of the present application applied to a terminal device side.
In a fourth aspect, this application provides a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by the processor, implements an image processing method according to any embodiment of this application.
In the above embodiment, the image processing apparatus obtains an image to be processed, performs contrast enhancement processing on the image to be processed to obtain a global enhanced image, determines a target local image of the image to be processed, performs contrast enhancement processing on the target local image to obtain a local enhanced image, fuses the local enhanced image and the global enhanced image to enable the local enhanced image to replace the position of the target local image in the global enhanced image to obtain a local enhanced global image of the image to be processed, and enhances local regions of the image to be processed and the target in the image to be processed respectively, so that the contrast of the global image can be maintained, the details and the contrast of the target region can be improved, and the local region of the target in the image to be processed is additionally enhanced and then fused with the global enhanced image, the blocky effect generated by local enhancement is avoided, the target can be highlighted, the local target concerned in the image is ensured to be more clearly presented, and the observation and the identification of human eyes are more convenient.
In the above embodiments, the computer readable storage medium and the corresponding image processing method embodiments belong to the same concept, and thus have the same technical effects as the corresponding image processing method embodiments, and are not described herein again.
Drawings
FIG. 1 is a diagram illustrating an application scenario of an image processing method according to an embodiment;
FIG. 2 is a diagram illustrating an application scenario of an image processing method according to another embodiment;
FIG. 3 is a diagram illustrating an application scenario of the image processing method in another embodiment;
FIG. 4 is a flow diagram of a method of image processing in one embodiment;
FIG. 5 is a schematic diagram of a Gaussian blur process in one embodiment;
FIG. 6 is a schematic diagram illustrating a comparison between an image to be processed and a corresponding locally enhanced global image according to an embodiment;
FIG. 7 is a flow chart of an alternative embodiment of an image processing method;
FIG. 8 is a logic diagram of the image processing method of FIG. 7;
FIG. 9 is a schematic diagram illustrating a comparison between an image to be processed and a corresponding locally enhanced global image according to another embodiment;
FIG. 10 is a diagram illustrating an exemplary embodiment of an image processing apparatus;
fig. 11 is a schematic structural diagram of an image processing apparatus in an embodiment.
Detailed Description
The technical solution of the present application is further described in detail with reference to the drawings and specific embodiments of the specification.
In order to make the objectives, technical solutions and advantages of the present application clearer, the present application will be described in further detail with reference to the attached drawings, the described embodiments should not be considered as limiting the present application, and all other embodiments obtained by a person of ordinary skill in the art without creative efforts shall fall within the protection scope of the present application.
In the following description, reference is made to the expression "some embodiments" which describe a subset of all possible embodiments, it being noted that "some embodiments" may be the same subset or different subsets of all possible embodiments, and may be combined with each other without conflict.
In the following description, references to the terms "first, second, and third" are only used to distinguish between similar items and do not denote a particular order, but rather the terms "first, second, and third" are used to indicate that a particular order or sequence of items may be interchanged where appropriate to enable embodiments of the application described herein to be practiced otherwise than as specifically illustrated or described herein.
Referring to fig. 1, a schematic view of an optional application scenario of the image processing method according to the embodiment of the present application is shown, where an image processing device 11 includes a processor 12, a memory 13 connected to the processor 12, and an infrared shooting module 14. The image processing device 11 acquires an infrared image in real time through the infrared shooting module 14 and sends the infrared image to the processor 12, the memory 13 stores a computer program for implementing the image processing method provided by the embodiment of the application, and the processor 12 processes the infrared image by executing the computer program to obtain a locally enhanced global image of the infrared image. The image processing device 11 may be various intelligent terminals which are integrated with the infrared shooting module 14 and have storage and processing functions, such as an infrared detector, a medical terminal device, an intelligent home device, a security camera device, and the like.
Referring to fig. 2, which is a schematic diagram of another optional application scenario of the image processing method, the image processing system includes an image processing device 21 and an infrared shooting module 22 communicatively connected to the image processing device 21. The image processing apparatus 21 includes a processor 211 and a memory 213 connected to the processor 211. The infrared shooting module 22 collects an infrared image in real time and sends the infrared image to the image processing device 21, a computer program for implementing the image processing method provided by the embodiment of the application is stored in a memory 213 of the image processing device 21, and the processor 211 processes the infrared image by executing the computer program to obtain a locally enhanced global image of the infrared image. The image processing device 21 may be various intelligent devices with communication and storage functions, such as: the smart phone, the desktop computer, the notebook computer, the tablet computer or other smart communication devices with network connection functions.
Referring to fig. 3, which is a schematic view of another optional application scenario of the image processing method, the image processing system includes a terminal device 31, a cloud 32, a gateway 33, and an image processing device 34. The terminal device 31 is a device having communication and storage functions, and includes: smart phones, desktop computers, notebook computers or other intelligent communication devices with network connection functions. Cloud 32 may include one or more physical servers, such as a network access server, a database server, a cloud server, and so forth. Optionally, the gateway 33 may be a gateway device built based on a network communication protocol, the image processing device 34 may access the network through the gateway 33 and be controlled by the terminal device 31, and the terminal device 31 is provided with a client capable of managing the image processing device 34, where the client may be an application client (such as a mobile phone APP), or a web client, such as an applet, a wechat public number, and the like, which is not limited herein. The user can control the image processing device 34 by operating the client, the terminal device 31 receives a control instruction input by the user for the image processing device 34 through the client, the control instruction is communicated with the cloud 32, and the cloud 32 forwards the control instruction input by the user to the corresponding image processing device 34 through the gateway 33, so that the remote intelligent control for the image processing device 34 is realized. The terminal device 31 may also receive, through the client, the operating parameter configuration information of the image processing device 34 input by the user, for example, the parameter threshold in the image enhancement processing performed by the image processing device 34 is configured or modified, and the image processing device 34 determines the current operating mode according to the operating parameter configuration information. For example: the terminal equipment can acquire infrared images in real time or send the infrared images stored locally to the image processing equipment, or the image processing equipment can acquire the issued infrared images from a gateway or a cloud end, and the image processing equipment processes the infrared images by executing the computer program to obtain the local enhanced global images of the infrared images.
Referring to fig. 4, an image processing method according to an embodiment of the present application may be applied to any image processing device in the application scenarios shown in fig. 1 to fig. 3. The image processing method comprises the following steps:
and S101, acquiring an image to be processed.
The image to be processed is an image which needs to be subjected to image enhancement processing, and the image to be processed can be a visible light image or an infrared image. Optionally, the image processing apparatus includes an image capturing module, and the acquiring the image to be processed includes: the image processing device acquires the image of the target scene in real time through the image shooting module. In other optional embodiments, the image processing apparatus does not include an image capturing module, and the acquiring the image to be processed includes: the image processing device acquires images sent by other intelligent devices with image shooting functions, wherein the other intelligent devices can be infrared detectors, mobile phone terminals, cloud terminals and the like.
S103, contrast enhancement processing is carried out on the image to be processed, and a global enhanced image is obtained.
The contrast enhancement processing on the image to be processed may be processing on the image to be processed by using a known contrast enhancement algorithm, such as a gray scale transformation method, a histogram adjustment method, and the like. And the image processing equipment performs contrast enhancement processing on the image to be processed to obtain an enhanced global enhanced image.
And S105, determining a target local image of the image to be processed, and performing contrast enhancement processing on the target local image to obtain a local enhanced image.
The target local image refers to an image of a part of area in the image to be processed, which is determined according to a preset rule, for example, the target local image may include at least one of the following situations: the image processing method comprises the steps of obtaining an image of an area where a target object is located in an image to be processed, obtaining an image corresponding to the position of a preset coordinate in the image to be processed, and obtaining an image corresponding to the position of a preset mark in the image to be processed. The image processing device determines a target local image according to the position of a target object by detecting the position of the target object in the image to be processed. The image processing method comprises the steps that an image corresponding to the position of a preset coordinate in an image to be processed is obtained, wherein the preset coordinate can be a preset coordinate point, the determined image area is expanded according to a set rule by taking the preset coordinate point as a reference position, and the image area is determined by taking the preset coordinate point as a center and taking a specified length as a radius; alternatively, the preset coordinates may be a plurality of preset coordinate points, and the image area may be covered by a geometric figure determined by using the plurality of coordinate points as vertexes. The image to be processed contains an image corresponding to the position of a preset mark, wherein the preset mark can be a mark for a user to manually circle a part to be highlighted in the image.
The contrast enhancement processing on the target local image may be processing on the target local image by using a known contrast enhancement algorithm, such as a gray scale transformation method, a histogram adjustment method, and the like. And the image processing equipment performs contrast enhancement processing on the target local image to obtain an enhanced local enhanced image.
S107, fusing the local enhanced image and the global enhanced image to enable the local enhanced image to replace the position of the target local image in the global enhanced image, and obtaining the local enhanced global image of the image to be processed.
Image Fusion (Image Fusion) refers to that Image data collected by a multi-source channel and related to the same target is processed by an Image processing technology, so that favorable information in respective channels is extracted to the maximum extent, and finally, high-quality images are synthesized, so that the utilization rate of Image information is improved, the computer interpretation precision and reliability are improved, the spatial resolution and the spectral resolution of an original Image are improved, and monitoring is facilitated. And the image processing equipment fuses the local enhanced image and the global enhanced image to enable the local enhanced image to replace the position of the target local image in the global enhanced image, so as to obtain the local enhanced global image of the image to be processed.
In the above embodiment, the image processing device enhances the image to be processed and the local region where the target is located in the image to be processed respectively, so that the global image contrast can be maintained, the details and the contrast of the target region can be improved, the local region where the target is located in the image to be processed is additionally enhanced and then fused with the global enhanced image, the local enhanced image replaces the position of the target local image in the global enhanced image, the locally enhanced global image of the image to be processed is obtained, the situation that the image to be processed is enhanced directly based on the enhanced display effect of the part to be highlighted to generate the block effect can be avoided, the target can be highlighted better, the local target concerned in the image can be presented more clearly, and the observation and the recognition of human eyes are facilitated.
In some embodiments, the performing contrast enhancement processing on the image to be processed to obtain a global enhanced image includes:
blurring the image to be processed to obtain a first blurred image, and determining a first detail map corresponding to the image to be processed according to an image difference value of the first blurred image and the image to be processed;
and carrying out contrast enhancement processing based on the first detail map to obtain a global enhanced image.
The image processing device processes an image to be processed to obtain a first detail map corresponding to the image to be processed, and performs contrast enhancement processing based on the first detail map to obtain a global enhanced image of the image to be processed, so that important detail information of the image can be improved, the dynamic range of image features corresponding to the important detail information in the image is increased, and the image features are easier to detect and recognize. The image processing device performs blurring processing on the image to be processed, which may be by using a known image blurring algorithm, such as: the image to be processed is subjected to blurring processing such as frame blurring (Box Blur), Kawase blurring (Kawase Blur), double blurring (Dual Blur), stray blurring (Bokeh Blur), Tilt Shift blurring (Tilt Shift Blur), Iris blurring (Iris Blur), granular blurring (Granny Blur), Radial blurring (Radial Blur), Directional blurring (Directional Blur), and the like, so that a first blurred image after the image to be processed is subjected to blurring processing is obtained.
In the above embodiment, the image processing device processes the image to be processed to obtain the corresponding first detail map, and performs contrast enhancement processing based on the first detail map of the image to be processed, so that the recognition degree of the important detail information of the image can be improved, the dynamic range of the image features of the important detail information in the image can be increased, and the enhanced image can be more suitable for the requirement of high quality of the image in a specific application.
Optionally, the blurring the image to be processed to obtain a first blurred image, and determining a first detail view corresponding to the image to be processed according to an image difference between the first blurred image and the image to be processed includes:
performing Gaussian blur on the image to be processed to obtain a first blurred image;
and determining a first detail map corresponding to the image to be processed according to the difference between the pixel value of the image to be processed and the pixel value of the first blurred image.
In this embodiment, a Gaussian Blur (Gaussian Blur) algorithm is used to perform Blur processing on the image to be processed, and the value of each pixel point in the image to be processed is replaced by the average value of surrounding pixels, please refer to fig. 5, which is a schematic diagram for determining the value of each pixel point by performing Gaussian Blur processing on the image to be processed, as shown in (a), a certain pixel point is used as a central point, the coordinates of the central point are (0,0), and the coordinates of the surrounding pixel points nearest to the central point are (-1,1), (0,1), (1,1), (-1,0), (-1, -1), (0, -1), (1, -1), the central point is used as an origin, and the weighted values σ are calculated according to the positions of other points on a normal curve, and the weighted average value is calculated according to the weighted values, determining a weight matrix corresponding to each point, as shown in (b); and (c) multiplying the gray value of each point by the corresponding weight value, and then adding the multiplied gray values to obtain the Gaussian blur value of the central point, as shown in (c). The image processing equipment calculates all pixel points in the image to be processed according to the method to obtain a first blurred image obtained after Gaussian blurring is performed on the image to be processed, and then obtains a first detail map corresponding to the image to be processed according to the difference between the value of each pixel point of the image to be processed and the value of the corresponding pixel point in the first blurred image.
In the above embodiment, the image processing device determines the first detail map corresponding to the image to be processed according to the difference between the pixel value of the image to be processed and the pixel value of the corresponding gaussian blurred image, so that image noise can be reduced, and the recognition degree of important detail information of the image can be better improved.
Optionally, the performing contrast enhancement processing based on the first detail map to obtain a global enhanced image includes:
determining the absolute value of a first pixel value difference value according to the difference between the pixel value of the image to be processed and the pixel value of the first blurred image;
accumulating the absolute value of the first pixel value difference value and the pixel value of the image to be processed to obtain a first detail histogram corresponding to the image to be processed;
and carrying out contrast enhancement processing based on the first detail histogram to obtain a global enhanced image.
The pixel value of the image to be processed may refer to a gray value of each pixel point of an original image of the image to be processed, the pixel value of the first blurred image may also refer to a gray value of each pixel point of the first blurred image, the pixel value of the image to be processed is represented as img, the pixel value of the first blurred image is represented as gsimg, the first pixel value difference value is represented as detail, the first pixel value difference value detail is equal to img-gsimg, the image processing device accumulates the absolute value of the first pixel value difference value and the pixel value of the image to be processed, and determines a first detail histogram corresponding to the image to be processed.
In the above embodiment, after the first detail map of the image to be processed is determined, the first detail histogram is determined by accumulating the pixel values of the first detail map by absolute values, and by providing an optional specific scheme for determining the first detail map and the first detail histogram of the image to be processed, the contrast enhancement processing is performed based on the first detail histogram, so that the recognition degree of important detail information of the image can be better improved, and the image quality after the enhancement processing is improved.
In some embodiments, the performing contrast enhancement processing based on the first detail histogram to obtain a global enhanced image includes:
performing equalization processing on the gray density and the gray space of the first detail histogram by adopting a double-platform histogram equalization algorithm to obtain the equalized first detail histogram;
and mapping the equalized first detail histogram by adopting a gray level transformation function to obtain a global enhanced image.
The double-platform histogram equalization algorithm is to perform equalization processing in 2 directions of the gray density and the gray space of the histogram simultaneously. The contrast of the original image can be obviously improved by the histogram gray level density equalization treatment; and (3) carrying out gray level spacing equalization processing on the basis of histogram density equalization, firstly counting the number Le of gray levels after the density equalization processing, actually carrying out accumulation calculation on the gray levels which are not zero in a gray level range to obtain effective actual degree levels, then reordering the effective gray levels, and carrying out equidistant arrangement in the whole gray level range. In an optional specific example, a dual-platform histogram equalization algorithm is used to perform equalization processing on the gray density and the gray space of the first detail histogram, and the first detail histogram after equalization processing is determined, which may be processed by the following formula:
wherein, TH is a high plateau value, TL is a low plateau value, when the gray value is larger than thre, the low plateau value is taken, when the gray value is larger than the high plateau value, the high plateau value is taken.
The gray level transformation is a method for changing the gray level value of each pixel in the original image point by point according to a certain transformation relation according to a certain target condition, and the gray level transformation function can be algorithms such as linear transformation, piecewise linear transformation, nonlinear transformation and the like.
In the above embodiment, the image processing apparatus performs equalization processing on the first detail histogram by using a dual-stage histogram equalization algorithm, sets the maximum cumulative upper limit value and the maximum cumulative lower limit value of a single point, and performs high-low stage limitation on the obtained first detail histogram, so that the background and noise of the image can be properly suppressed, and better equalization can be obtained.
In some embodiments, before performing contrast enhancement processing on the image to be processed to obtain a global enhanced image, the method includes:
and carrying out time domain denoising and space domain denoising on the image to be processed to obtain the denoised image to be processed.
The time domain denoising can select an FIR filtering algorithm, and the spatial domain denoising can select an NL-means filtering algorithm. The image processing equipment carries out time domain denoising on the image to be processed by adopting an FIR filtering algorithm, so that the stability of image filtering processing can be improved, and the calculation error is reduced; the NL-means filtering algorithm is adopted to carry out spatial domain denoising on the image to be processed, so that the calculation amount can be reduced.
In some embodiments, the acquiring the image to be processed includes:
acquiring a 14bit infrared image which is output by an infrared shooting module and quantized through analog-to-digital conversion;
before the contrast enhancement processing is performed on the image to be processed to obtain a global enhanced image, the method further includes:
and carrying out wide dynamic mapping on the denoised 14bit infrared image to obtain an 8bit infrared image as the image to be processed.
The image to be processed is an infrared image collected and output by the infrared shooting module. The image processing equipment is used for carrying out denoising processing on the 14bit infrared image by acquiring the 14bit infrared image which is output by the infrared shooting module and subjected to analog-to-digital conversion quantization, carrying out wide dynamic mapping on the denoised 14bit infrared image to obtain an 8bit infrared image serving as the image to be processed, and mapping the 14bit infrared image to an 8bit gray scale space by mapping the 14bit infrared image so that the image subjected to mapping processing can be displayed on a display screen.
In the above embodiment, before performing contrast enhancement on the image to be processed, the image processing device performs denoising on the image to be processed, and performs wide dynamic mapping on the denoised image so as to map the denoised image to an 8-bit infrared image suitable for being displayed on a display screen, so that a local enhanced global image obtained by performing enhancement on the image to be processed and a target local image respectively and then fusing the two images can be displayed on the display screen, thereby satisfying the visualization requirement and facilitating visual understanding of the image processing effect.
In some embodiments, the determining a target local image of the image to be processed, and performing contrast enhancement processing on the target local image to obtain a locally enhanced image includes:
determining a target local image of the image to be processed;
blurring the target local image to obtain a second blurred image, and determining a second detail image corresponding to the target local image according to an image difference value between the second blurred image and the target local image;
and carrying out contrast enhancement processing based on the second detail map to obtain a local enhanced image.
The image processing device determines a target local image of the image to be processed and performs additional enhancement processing on the target local image. The process of contrast enhancement processing on the target local image by the image processing equipment and the process of contrast enhancement processing on the image to be processed by the image processing equipment can be the same, and the difference is that the values of the parameter threshold are different; it should be noted that, in some optional embodiments, an implementation manner of performing, by the image processing apparatus, contrast enhancement processing on the target local image may also be different from a flow of performing, by the image processing apparatus in the foregoing embodiments, contrast enhancement processing on the image to be processed, for example, a known contrast enhancement processing manner such as direct pixel-based adjustment may be used. In the embodiment of the present application, the image processing device performs blurring processing on the target local image, or may use a known image blurring algorithm, such as: and carrying out blurring processing on the target local image by using frame blurring (Box Blur), Kawase blurring (Kawase Blur), double blurring (Dual Blur), stray blurring (Bokeh Blur), Tilt Shift blurring (Tilt Shift Blur), Iris blurring (Iris Blur), granular blurring (Granny Blur), Radial blurring (Radial Blur), Directional blurring (Directional Blur) and the like to obtain a second blurred image after blurring processing on the target local image. The image processing equipment performs fuzzy processing on the target local image, determines a second detail image according to the image difference value between the image subjected to the fuzzy processing and the original image, performs contrast enhancement processing on the basis of the second detail image to obtain an enhanced image of the target local image, can highlight important detail information in the target local image, and increases the dynamic range of image features corresponding to the important detail information in the image, so that the image features are more easily detected and identified.
In some embodiments, the determining a target local image of the image to be processed includes:
identifying a target object in the image to be processed, and determining a target local image according to the position of the target object; and/or the presence of a gas in the gas,
determining a target local image of the image to be processed based on the set image coordinates; and/or the presence of a gas in the gas,
and determining a target local image of the image to be processed according to a preset image mark in the image to be processed.
The method for determining the target local image in the image to be processed by the image processing device comprises the following steps: determining a target local image according to the position of a target object by identifying the target object in an image to be processed; determining a target local image of the image to be processed based on the set image coordinates; and determining a target local image of the image to be processed according to a preset image mark in the image to be processed. In the implementation, one of the modes may be selected by a user, or a target partial image in an image to be processed may be selected by the image processing apparatus according to a set priority order.
The image processing device may identify a target object in an image to be processed, extract image features in the image to be processed through an image identification model, and determine a type and a corresponding position of the target object included in the image to be processed based on the image features. The image processing apparatus may determine the target partial image based on the set image coordinates, with an image area defined with the set image coordinates as a center and a set length as a radius as the target partial image. The image processing device may determine the target local image according to a preset image marker in the image to be processed, identify the image marker in the image to be processed, and use an image area correspondingly covered by the image marker as the target local image. Referring to fig. 6, an optional specific example is shown, in which a target local image of the to-be-processed image is determined based on set image coordinates, and the to-be-processed image and the target local image are respectively subjected to contrast enhancement processing and then fused to obtain an effect schematic diagram of a locally enhanced global image.
In the above embodiment, the image processing device may determine the target local image of the image to be processed in one or more ways, perform additional enhancement processing on the target local image, and replace the image after the local enhancement processing with the image after the local enhancement processing in the global image portion, so as to improve the detail contrast of the target area.
In some embodiments, the blurring the target local image to obtain a second blurred image, and determining a second detail map corresponding to the target local image according to an image difference between the second blurred image and the target local image includes:
performing Gaussian blur on the target local image to obtain a second blurred image;
and determining a second detail map corresponding to the target local image according to the difference between the pixel value of the target local image and the pixel value of the second blurred image.
In this embodiment, a Gaussian Blur (Gaussian Blur) algorithm is used to perform a Gaussian Blur on the target local image to obtain a second blurred image, a specific implementation process of determining the second detail map corresponding to the target local image is the same as a specific implementation process of determining the first detail map corresponding to the image to be processed by the image processing device according to a difference between a pixel value of the target local image and a pixel value of the second blurred image, so that details are not repeated here.
In the above embodiment, the image processing device determines the second detail map corresponding to the target local image according to the difference between the pixel value of the target local image and the pixel value of the corresponding gaussian blurred image, so that image noise can be reduced, and the identification degree of important detail information in the to-be-highlighted part image in the image can be better improved.
Optionally, the performing contrast enhancement processing based on the second detail map to obtain a locally enhanced image includes:
determining the absolute value of a second pixel value difference value according to the difference between the pixel value of the target local image and the pixel value of the second blurred image;
accumulating the absolute value of the second pixel value difference value and the pixel value of the target local image to obtain a second detail histogram corresponding to the target local image;
and performing contrast enhancement processing on the basis of the second detail histogram to obtain a local enhanced image.
The pixel value of the target local image may refer to a gray value of each pixel point at a position where the target local image is located in the original image to be processed, the pixel value of the second blurred image may also refer to a gray value of each pixel point of the second blurred image correspondingly, the pixel value of the target local image is represented as G-img, the pixel value of the second blurred image is represented as G-gsimg, the second pixel value difference is represented as G-detail, the second pixel value difference G-detail is equal to G-img-G-gsimg, the image processing device accumulates the absolute value of the second pixel value difference and the pixel value of the target local image, and determines a second detail histogram corresponding to the target local image.
In the foregoing embodiment, after the second detail view of the target local image is determined, the second detail view corresponding to the target local image is determined by accumulating the pixel values of the second detail view by absolute values.
Optionally, the performing contrast enhancement processing based on the second detail histogram to obtain a locally enhanced image includes:
performing equalization processing on the gray density and the gray space of the second detail histogram by adopting a double-platform histogram equalization algorithm to obtain the equalized second detail histogram;
and mapping the equalized second detail histogram by adopting a gray level transformation function to obtain a local enhanced image.
The double-platform histogram equalization algorithm is to perform equalization processing in 2 directions of the gray density and the gray space of the histogram simultaneously. The image processing equipment firstly performs histogram gray density equalization processing on a second detail histogram of the target local image so as to improve the contrast of the original target local image; and then carrying out gray level interval equalization processing on the basis of density equalization of the second detail histogram, firstly counting the number Le of gray levels after the density equalization processing, and actually carrying out accumulation calculation on the gray levels which are not zero in a gray level range to obtain effective actual degree levels, then reordering the effective gray levels, and carrying out equidistant arrangement in the whole gray level range to avoid overhigh local brightness. In an optional specific example, a manner of performing equalization processing on the gray scale density and the gray scale interval of the second detail histogram of the local target image by using a dual-stage histogram equalization algorithm is the same as a manner of performing equalization processing on the gray scale density and the gray scale interval of the first detail histogram of the image to be processed by using a dual-stage histogram equalization algorithm by using an image processing device, but a difference is that a high stage value can be increased according to a ratio of a part to be highlighted in the target local image, so that the contrast of the target local image can be further improved, and the problem of excessive stretching can be avoided.
In the above embodiment, the image processing apparatus performs the equalization processing on the second detail histogram of the target local image by using a dual-platform histogram equalization algorithm, sets the maximum accumulation upper limit value and the lower limit value of the single point, performs the high-low platform limitation on the obtained second detail histogram, and may select different parameter threshold values for processing the image to be processed according to the image occupation ratio of the to-be-highlighted portion, so that the target local image is subjected to additional and independent enhancement processing, thereby improving the details and the contrast of the region where the to-be-highlighted portion is located without causing the overall overstretching of the image.
In order to more fully understand the image processing method provided in the embodiment of the present application, please refer to fig. 7 to 9, which take an image to be processed as an infrared image as an example, and describe the image processing method.
S11, acquiring an infrared image, and denoising the infrared image; the denoising processing comprises time domain denoising and space domain denoising, an FIR filter is selected for the time domain denoising, the time domain denoising can have higher stability and smaller calculation error, and the NL-means algorithm after optimization is selected for the space domain denoising, so that the calculation amount can be reduced, and the image processing algorithm can be realized based on the FPGA;
s12, carrying out wide dynamic mapping on the denoised infrared image; the infrared image is 14bit data, and is mapped to 8 bits through wide dynamic mapping so as to be displayed on a display screen;
s13, performing Gaussian blur on a wide dynamic infrared image to obtain a first blurred image, obtaining a first detail map of the infrared image according to the difference between the pixel values of the infrared image original image and the first blurred image, and performing remapping by adopting a dual-platform histogram equalization algorithm based on the first detail map to obtain an enhanced global image; the contrast enhancement processing is carried out by adopting the detail map, so that the gray value with rich details has larger proportion and the details are easier to highlight;
s14, determining a local image of the area where the part to be highlighted in the infrared image is located;
s15, performing Gaussian blur on the local image to obtain a second blurred image, obtaining a second detail map of the local image according to the difference between the pixel values of the local image original image and the second blurred image, and remapping the second detail map by adopting a double-platform histogram equalization algorithm to obtain an enhanced local image; in a double-platform histogram equalization algorithm adopted for contrast enhancement of a local image, values of a high platform value and a low platform value are different from values of a high platform value and a low platform value in contrast enhancement of an infrared image, so that details of a part to be highlighted are clearer and more distinguishable, and the over-stretching of the whole image of the infrared image is avoided;
s16, fusing the enhanced local image and the enhanced global image, and replacing the corresponding position of the global image with the enhanced local image; therefore, the part where the target exists can be displayed in the image more clearly, and the target is more easily highlighted while the global image is not stretched; and secondly, directly replacing the corresponding part of the locally enhanced image in the global image with the locally enhanced image, so that the target details in the obtained fusion image are richer and the contrast is better.
The image processing method provided in the above embodiment at least has the following features:
firstly, contrast enhancement processing is respectively carried out on the whole infrared image and a local image of a region where a target to be highlighted is located, and the region where the target is located is additionally and independently enhanced, so that the block effect caused by a local enhancement algorithm can be avoided;
secondly, global image contrast is kept, and the influence on the image effect due to the fact that the overall image is excessively stretched can be avoided while the details and the contrast of a target area are improved;
thirdly, through the fusion of the enhanced global image and the enhanced local image, the area of the target to be highlighted can be independently displayed, and the target can be observed and recognized by human eyes more conveniently.
Referring to fig. 10, in another aspect of the present application, an image processing apparatus is provided, which may be implemented by using an infrared detector in an exemplary embodiment. The image processing apparatus includes: an obtaining module 1121 configured to obtain an image to be processed; a first enhancement processing module 1122, configured to perform contrast enhancement processing on the image to be processed to obtain a global enhanced image; the second enhancement processing module 1123 is configured to determine a target local image of the image to be processed, and perform contrast enhancement processing on the target local image to obtain a locally enhanced image; a fusion module 1124, configured to fuse the locally enhanced image and the globally enhanced image, so that the locally enhanced image replaces the position of the target local image in the globally enhanced image, thereby obtaining a locally enhanced global image of the image to be processed.
The first enhancement processing module 1122 is specifically configured to perform blurring processing on the image to be processed to obtain a first blurred image, and determine a first detail map corresponding to the image to be processed according to an image difference between the first blurred image and the image to be processed; and carrying out contrast enhancement processing based on the first detail map to obtain a global enhanced image.
The first enhancement processing module 1122 is further configured to perform gaussian blur on the image to be processed to obtain a first blurred image; and determining a first detail map corresponding to the image to be processed according to the difference between the pixel value of the image to be processed and the pixel value of the first blurred image.
The first enhancement processing module 1122 is further configured to determine an absolute value of a first pixel value difference according to a difference between a pixel value of the image to be processed and a pixel value of the first blurred image; and accumulating the absolute value of the first pixel value difference value and the pixel value of the image to be processed to obtain a first detail histogram corresponding to the image to be processed.
The first enhancement processing module 1122 is further configured to perform equalization processing on the gray scale density and the gray scale interval of the first detail histogram by using a dual-platform histogram equalization algorithm to obtain the equalized first detail histogram; and mapping the equalized first detail histogram by adopting a gray level transformation function to obtain a global enhanced image.
The image processing device further comprises a preprocessing module, which is used for performing time domain denoising and space domain denoising on the image to be processed to obtain the denoised image to be processed.
The preprocessing module is also used for acquiring a 14bit infrared image which is output by the infrared shooting module and quantized through analog-to-digital conversion; and carrying out wide dynamic mapping on the denoised 14bit infrared image to obtain an 8bit infrared image as the image to be processed.
The second enhancement processing module 1123 is specifically configured to determine a target local image of the image to be processed; blurring the target local image to obtain a second blurred image, and determining a second detail image corresponding to the target local image according to an image difference value between the second blurred image and the target local image; and carrying out contrast enhancement processing based on the second detail map to obtain a local enhanced image.
The second enhancement processing module 1123 is further configured to identify a target object in the image to be processed, and determine a target local image according to a position of the target object; and/or determining a target local image of the image to be processed based on the set image coordinates; and/or determining a target local image of the image to be processed according to a preset image mark in the image to be processed.
The second enhancement processing module 1123 is further configured to perform gaussian blur on the target local image to obtain a second blurred image; and determining a second detail map corresponding to the target local image according to the difference between the pixel value of the target local image and the pixel value of the second blurred image.
Wherein the second enhancement processing module 1123 is further configured to determine an absolute value of a second pixel value difference according to a difference between a pixel value of the target local image and a pixel value of the second blurred image; and accumulating the absolute value of the second pixel value difference value and the pixel value of the target local image to obtain a second detail histogram corresponding to the target local image.
The second enhancement processing module 1123 is further configured to perform equalization processing on the gray scale density and the gray scale interval of the second detail histogram by using a dual-platform histogram equalization algorithm, so as to obtain the equalized second detail histogram; and mapping the equalized second detail histogram by adopting a gray level transformation function to obtain a local enhanced image.
It should be noted that: in the process of implementing the local image enhancement processing, the image processing apparatus provided in the above embodiment is exemplified by only the division of the above program modules, and in practical applications, the processing may be distributed to be completed by different program modules according to needs, that is, the internal structure of the apparatus may be divided into different program modules, so as to complete all or part of the above described method steps. In addition, the image processing apparatus and the image processing method provided by the above embodiments belong to the same concept, and specific implementation processes thereof are described in the method embodiments in detail and are not described herein again.
Referring to fig. 11, an optional hardware structure diagram of the image processing apparatus provided in the embodiment of the present application is provided, where the image processing apparatus includes a processor 111 and a memory 112 connected to the processor 111, and the memory 112 is used for storing various types of data to support operations of an image processing device and storing a computer program for implementing the image processing method provided in any embodiment of the present application, and when the computer program is executed by the processor, the steps of the image processing method provided in any embodiment of the present application are implemented, and the same technical effects can be achieved, and are not described herein again to avoid repetition.
Optionally, the image processing apparatus further includes an infrared shooting module 113 connected to the processor 111, where the infrared shooting module 113 is configured to shoot an infrared image and send the infrared image to the processor 111 as an image to be processed.
An embodiment of the present application further provides a computer-readable storage medium, where a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the computer program implements each process of the above-mentioned embodiment of the image processing method, and can achieve the same technical effect, and in order to avoid repetition, details are not repeated here. The computer-readable storage medium may be a Read-only memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
Through the above description of the embodiments, those skilled in the art will clearly understand that the method of the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but in many cases, the former is a better implementation manner. Based on such understanding, the technical solutions of the present invention may be embodied in the form of a software product, which is stored in a storage medium (such as ROM/RAM, magnetic disk, optical disk) and includes instructions for enabling a terminal (such as a mobile phone, a computer, a server, an air conditioner, or a network device) to execute the method according to the embodiments of the present invention.
The above description is only for the specific embodiments of the present application, but the scope of the present application is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present application, and shall be covered by the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
Claims (11)
1. An image processing method applied to an image processing apparatus, comprising:
acquiring an image to be processed;
carrying out contrast enhancement processing on the image to be processed to obtain a global enhanced image;
determining a target local image of the image to be processed, and performing contrast enhancement processing on the target local image to obtain a local enhanced image;
and fusing the local enhanced image and the global enhanced image to enable the local enhanced image to replace the position of the target local image in the global enhanced image, so as to obtain the local enhanced global image of the image to be processed.
2. The image processing method of claim 1, wherein performing contrast enhancement processing on the image to be processed to obtain a global enhanced image comprises:
blurring the image to be processed to obtain a first blurred image, and determining a first detail map corresponding to the image to be processed according to an image difference value of the first blurred image and the image to be processed;
performing contrast enhancement processing based on the first detail map to obtain a global enhanced image; and/or the presence of a gas in the gas,
the determining a target local image of the image to be processed, and performing contrast enhancement processing on the target local image to obtain a locally enhanced image includes:
determining a target local image of the image to be processed;
blurring the target local image to obtain a second blurred image, and determining a second detail image corresponding to the target local image according to an image difference value between the second blurred image and the target local image;
and carrying out contrast enhancement processing based on the second detail map to obtain a local enhanced image.
3. The image processing method according to claim 2, wherein the blurring the image to be processed to obtain a first blurred image, and determining a first detail map corresponding to the image to be processed according to an image difference between the first blurred image and the image to be processed includes:
performing Gaussian blur on the image to be processed to obtain a first blurred image;
determining a first detail map corresponding to the image to be processed according to the difference between the pixel value of the image to be processed and the pixel value of the first blurred image; or the like, or, alternatively,
the blurring processing of the target local image to obtain a second blurred image, and determining a second detail map corresponding to the target local image according to an image difference between the second blurred image and the target local image includes:
performing Gaussian blur on the target local image to obtain a second blurred image;
and determining a second detail map corresponding to the target local image according to the difference between the pixel value of the target local image and the pixel value of the second blurred image.
4. The image processing method according to claim 2, wherein performing contrast enhancement processing based on the first detail map to obtain a global enhanced image comprises:
determining the absolute value of a first pixel value difference value according to the difference between the pixel value of the image to be processed and the pixel value of the first blurred image;
accumulating the absolute value of the first pixel value difference value and the pixel value of the image to be processed to obtain a first detail histogram corresponding to the image to be processed;
performing contrast enhancement processing based on the first detail histogram to obtain a global enhanced image; or the like, or, alternatively,
performing contrast enhancement processing based on the second detail map to obtain a locally enhanced image, including:
determining the absolute value of a second pixel value difference value according to the difference between the pixel value of the target local image and the pixel value of the second blurred image;
accumulating the absolute value of the second pixel value difference value and the pixel value of the target local image to obtain a second detail histogram corresponding to the target local image;
and performing contrast enhancement processing on the basis of the second detail histogram to obtain a local enhanced image.
5. The image processing method according to claim 4, wherein performing contrast enhancement processing based on the first detail histogram to obtain a global enhanced image comprises:
performing equalization processing on the gray density and the gray space of the first detail histogram by adopting a double-platform histogram equalization algorithm to obtain the equalized first detail histogram;
mapping the first detail histogram after the equalization processing by adopting a gray level transformation function to obtain a global enhanced image; or the like, or, alternatively,
performing contrast enhancement processing based on the second detail histogram to obtain a locally enhanced image, including:
performing equalization processing on the gray density and the gray space of the second detail histogram by adopting a double-platform histogram equalization algorithm to obtain the equalized second detail histogram;
and mapping the equalized second detail histogram by adopting a gray level transformation function to obtain a local enhanced image.
6. The image processing method of claim 1, wherein before performing contrast enhancement processing on the image to be processed to obtain a global enhanced image, the method comprises:
and carrying out time domain denoising and space domain denoising on the image to be processed to obtain the denoised image to be processed.
7. The image processing method of claim 6, wherein the acquiring the image to be processed comprises:
acquiring a 14bit infrared image which is output by an infrared shooting module and quantized through analog-to-digital conversion;
before the contrast enhancement processing is performed on the image to be processed to obtain a global enhanced image, the method further includes:
and carrying out wide dynamic mapping on the denoised 14bit infrared image to obtain an 8bit infrared image as the image to be processed.
8. The image processing method according to claim 1, wherein the determining the target local image of the image to be processed includes:
identifying a target object in the image to be processed, and determining a target local image according to the position of the target object; and/or the presence of a gas in the gas,
determining a target local image of the image to be processed based on the set image coordinates; and/or the presence of a gas in the gas,
and determining a target local image of the image to be processed according to a preset image mark in the image to be processed.
9. An image processing apparatus characterized by comprising:
the acquisition module is used for acquiring an image to be processed;
the first enhancement processing module is used for carrying out contrast enhancement processing on the image to be processed to obtain a global enhanced image;
the second enhancement processing module is used for determining a target local image of the image to be processed and carrying out contrast enhancement processing on the target local image to obtain a local enhanced image;
and the fusion module is used for fusing the local enhanced image and the global enhanced image to enable the local enhanced image to replace the position of the target local image in the global enhanced image so as to obtain the local enhanced global image of the image to be processed.
10. An image processing apparatus comprising a processor, a memory connected to the processor, and a computer program stored on the memory and executable by the processor, the computer program, when executed by the processor, implementing the image processing method of any one of claims 1 to 8.
11. A computer-readable storage medium, characterized in that a computer program is stored thereon, which computer program, when being executed by the processor, realizes the image processing method according to any one of claims 1 to 8.
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