CN116452447A - Low-illumination high-definition image processing method - Google Patents
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Abstract
The invention relates to the technical field of image processing, in particular to a low-illumination high-definition image processing method, which comprises the following steps: respectively solving a bright channel image and a dark channel image of the low-illumination image by using a bright channel prior and a dark channel prior; and obtaining a self-adaptive atmospheric illumination map through the bright channel image. According to the low-illumination high-definition image processing method, the accurate edge map of the gray map is calculated by calculating the gray map of the input original image: calculating gradient amplitude values of the bright pixel points and the dark pixel points of the gray level map by adopting different edge detection operators respectively to obtain a rough edge map; denoising, repairing and refining the rough edge map to obtain a precise edge map, and calculating an illumination map according to the gray map and the precise edge map: and subtracting the gray value of the corresponding pixel point in the accurate edge map from the gray value of each pixel point of the gray map in the logarithmic domain.
Description
Technical Field
The invention relates to the technical field of image processing, in particular to a low-illumination high-definition image processing method.
Background
With the rapid development of computer technology and ARM technology, image processing is widely applied in various application fields such as aerospace, military, biomedicine and artificial intelligence, image enhancement provides a key step for image processing, and for pictures in dark environments, many unknown contents cannot be displayed, which leads to important information loss, such as the fields of traffic conditions of video monitoring shooting, daily color image processing, images of ships and night criminals, mine images and the like in low-illumination conditions such as night and darkness, so that the research on the low-illumination image enhancement method is very valuable.
In normal use, shooting is performed by a star light level low-illumination 200W high definition, auxiliary shooting is performed by an electronic red dot and a dividing line, and auxiliary shooting is performed by AI intelligent recognition tracking, a gray level conversion method represented by a histogram equalization method, a homomorphic filtering method based on an illumination-reflection model, a gradient domain enhancement method, a retinex enhancement method and the like are performed on the shot image, the gray level distribution of the image can be more uniform and the contrast of the image is enhanced by the gray level conversion method represented by the histogram equalization method, but the frequency information and the detail information of the image are not considered, an over-enhanced image is easy to generate, the image is divided into a high frequency part and a low frequency part by the homomorphic filtering method based on the illumination-reflection model, filtering is performed to achieve the purpose of enhancing the contrast of the image and simultaneously compressing the dynamic range of the image, but the over-enhancement phenomenon occurs, the gradient domain enhancement method processes the gradient of the original image by reducing the gradient value of the image, and enhancing the image edge by increasing the local gradient value, and the image edge has the defects that the image is more uniform to a certain extent, and the image is not suitable for a real-time algorithm in the gradient domain reconstruction.
Disclosure of Invention
(one) solving the technical problems
Aiming at the defects of the prior art, the invention provides a low-illumination high-definition image processing method which has the advantages of clearer imaging, high practicability and the like, and solves the problem of low imaging definition in post-processing shooting.
(II) technical scheme
In order to achieve the purposes of clearer imaging and high practicability, the invention provides the following technical scheme: a low-illuminance high-definition image processing method, the method comprising the steps of:
1) Respectively solving a bright channel image and a dark channel image of the low-illumination image by using a bright channel prior and a dark channel prior;
2) Obtaining a self-adaptive atmospheric illumination map through the bright channel image;
3) Obtaining a self-adaptive transfer function diagram through the dark channel image and the self-adaptive atmospheric illumination diagram;
4) Restoring a scene image according to the low-illumination image, the self-adaptive atmospheric illumination map and the self-adaptive transfer function map in the atmospheric scattering physical model, wherein the restored scene image is determined according to the following expression:
J(x)＝I(x)-A(x)A(x)(max(t(x),t0))+1；
wherein x represents two-dimensional space coordinates, J (x) is a restored scene image, I (x) is a low-illumination image, A (x) is an adaptive atmospheric illumination map, t (x) is an adaptive transfer function map, and t0 has a value of 0.1.
Preferably, in step 1), the specific method for respectively obtaining the bright channel image and the dark channel image of the low-illumination image by using the bright channel prior and the dark channel prior includes:
and (3) obtaining a bright channel image of the low-illumination image by using the bright channel prior:
when the low-illumination image is a gray image, the gray low-illumination image is used as a guide image of a GuidedFilter filter;
the guide image is determined according to the following expression:
Iguide(x)＝I(x)；
wherein Iguide (x) is a guide image, and I (x) is a gray-scale low-illumination image;
performing maximum filtering on the obtained guide image to obtain a rough extracted bright channel image;
the coarsely extracted bright channel image is determined according to the following expression:
Ilig(x)＝maxx∈Ω(x)(Iguide(x))；
wherein Ilig (x) is a rough extracted bright channel image, x is a two-dimensional space coordinate, and Ω (x) is a square neighborhood centered on the coordinate x;
when the low-illumination image is a color image, calculating the maximum value of R, G, B color channels at each pixel point of the color low-illumination image as a guide image of a GuidedFilter filter;
the guide image is determined according to the following expression:
Iguide(x)＝maxc∈{R,G,B}(Ic(x))；
wherein Iguide (x) is a guide image, c is a color channel, c E { R, G, B } are R, G, B color channels, and Ic is a color channel of a color low-illumination image;
performing maximum filtering on the obtained guide image to obtain a rough extracted bright channel image;
the coarsely extracted bright channel image is determined according to the following expression:
Ilig(x)＝maxx∈Ω(x)(Iguide(x))；
wherein Ilig (x) is a rough extracted bright channel image, x is a two-dimensional space coordinate, and Ω (x) is a square neighborhood centered on the coordinate x;
and (3) carrying out edge-preserving smooth filtering on the rough extracted bright channel image through a GuidedFilter filter by utilizing the guide image, and finally obtaining a refined bright channel image Ilight (x).
Preferably, in step 3), the process comprises,
the specific method for obtaining the self-adaptive transfer function diagram through the dark channel image and the self-adaptive atmospheric illumination diagram comprises the following steps:
obtaining an adaptive transfer function diagram by using the dark channel image and the adaptive atmospheric illumination diagram;
the adaptive transfer function map is determined according to the following expression:
idark (x) =A (x) (1-t (x)), namely: t (x) =1-widmark (x) a (x);
wherein t (x) is an adaptive transfer function diagram, w is a correction factor, and 0 < w is less than or equal to 1, so as to reserve a small part of dark area and increase the depth perception of a scene, and w=0.95 is taken here.
Preferably, in step 4), the specific method for restoring the scene image according to the low-illumination image, the adaptive atmospheric illumination map and the adaptive transfer function map in the atmospheric scattering physical model is as follows: restoring the scene image through the atmospheric scattering physical model by utilizing the low-illumination image, the self-adaptive atmospheric illumination map and the self-adaptive transfer function map;
the restored scene image is determined according to the following expression:
J(x)＝I(x)-A(x)A(x)(max(t(x),t0))+1；
wherein J (x) is a restored scene image, I (x) is a low-illumination image, A (x) is an adaptive atmospheric illumination image, t (x) is an adaptive transfer function image, and t0 has a value of 0.1, so as to avoid that the scene image J (x) contains too much noise when t0 tends to 0
And outputting the formed image through the Wifi module.
Preferably, the method comprises the steps of:
calculating a gray scale map of the input original image;
calculating an accurate edge map of the gray map: calculating gradient amplitude values of the bright pixel points and the dark pixel points of the gray level map by adopting different edge detection operators respectively to obtain a rough edge map; denoising, repairing and refining the rough edge map to obtain an accurate edge map;
calculating an illumination map according to the gray level map and the accurate edge map: subtracting the gray value of the corresponding pixel point in the accurate edge map from the gray value of each pixel point of the gray map in the logarithmic domain to obtain an illumination map in the logarithmic domain;
adjusting the contrast of the illumination map;
synthesizing an enhanced gray scale image according to the accurate edge image and the illumination image with adjusted contrast: in the logarithmic domain, adding the gray value of each pixel point of the accurate edge map with the gray value of the corresponding pixel point in the illumination map after the contrast adjustment to obtain a gray map with enhanced brightness in the logarithmic domain;
and calculating and outputting the enhanced color image according to the enhanced gray level image.
Preferably, refining the rough edge map after repair to obtain a precise edge map includes:
initializing all pixel points of the I' edge to be 0;
the pixel points are reassigned by adopting the following method:
1) If Iedge (x, y) is 0 and Iedge (x+1, y) is 1, then Iedge' (x+M, y) is 1;
2) If Iedge (x, y) is 0 and Iedge (x, y+1) is 1, then I' edge (x, y+M) is 1;
preferably, where (x, y) is the current pixel point, M represents the half width or half height of the template used in repairing the edge map, iedge represents the rough edge map after repairing, and I' edge represents the precise edge map.
(III) beneficial effects
Compared with the prior art, the invention provides a low-illumination high-definition image processing method, which has the following beneficial effects:
1. according to the low-illumination high-definition image processing method, the accurate edge map of the gray map is calculated by calculating the gray map of the input original image: calculating gradient amplitude values of the bright pixel points and the dark pixel points of the gray level map by adopting different edge detection operators respectively to obtain a rough edge map; denoising, repairing and refining the rough edge map to obtain a precise edge map, and calculating an illumination map according to the gray map and the precise edge map: subtracting the gray value of the corresponding pixel point in the accurate edge map from the gray value of each pixel point of the gray map in the logarithmic domain to obtain an illumination map in the logarithmic domain, adjusting the contrast of the illumination map, and synthesizing an enhanced gray map according to the accurate edge map and the illumination map with the contrast adjusted: and in the logarithmic domain, adding the gray value of each pixel point of the accurate edge map with the gray value of the corresponding pixel point in the illumination map after the contrast adjustment to obtain a gray map with enhanced brightness on the logarithmic domain, calculating and outputting an enhanced color image according to the enhanced gray map, shooting by using a starlight level low-illumination 200W high definition, and carrying out auxiliary shooting by using an electronic red point and a dividing line, wherein AI intelligent identification tracking is arranged for carrying out auxiliary shooting.
2. According to the low-illumination high-definition image processing method, the rough edge map after repair is refined, and the obtaining of the accurate edge map comprises the following steps: initializing all pixel points of the I' edge to be 0, and reassigning the pixel points by adopting the following method:
1) If Iedge (x, y) is 0 and Iedge (x+1, y) is 1, then Iedge' (x+M, y) is 1;
2) If Iedge (x, y) is 0 and Iedge (x, y+1) is 1, then I' edge (x, y+M) is 1;
wherein, (x, y) is the current pixel point, M represents half width or half height of the template used for repairing the edge map, iedge represents the rough edge map after repairing, and I' edge represents the accurate edge map.
Drawings
FIG. 1 is a flow chart of a low-illumination high-definition image processing method according to the present invention;
FIG. 2 is a flowchart of a refined bright/dark channel image of a low-illumination high-definition image processing method according to the present invention;
fig. 3 is a flowchart of image enhancement of a low-illumination high-definition image processing method according to the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1-3, a low-illumination high-definition image processing method includes the following steps:
1) Respectively solving a bright channel image and a dark channel image of the low-illumination image by using a bright channel prior and a dark channel prior;
2) Obtaining a self-adaptive atmospheric illumination map through the bright channel image;
3) Obtaining a self-adaptive transfer function diagram through the dark channel image and the self-adaptive atmospheric illumination diagram;
4) Restoring a scene image according to the low-illumination image, the self-adaptive atmospheric illumination map and the self-adaptive transfer function map in the atmospheric scattering physical model, wherein the restored scene image is determined according to the following expression:
J(x)＝I(x)-A(x)A(x)(max(t(x),t0))+1；
wherein x represents two-dimensional space coordinates, J (x) is a restored scene image, I (x) is a low-illumination image, A (x) is an adaptive atmospheric illumination map, t (x) is an adaptive transfer function map, and t0 has a value of 0.1.
When the method is used, the gray level diagram of an input original image is calculated, the accurate edge diagram of the gray level diagram is calculated, and different edge detection operators are respectively adopted for the bright pixel points and the dark pixel points of the gray level diagram to calculate gradient amplitude values, so that a rough edge diagram is obtained; denoising, repairing and refining the rough edge map to obtain a precise edge map, and calculating an illumination map according to the gray map and the precise edge map: subtracting the gray value of the corresponding pixel point in the accurate edge map from the gray value of each pixel point of the gray map in the logarithmic domain to obtain an illumination map in the logarithmic domain, adjusting the contrast of the illumination map, and synthesizing an enhanced gray map according to the accurate edge map and the illumination map with the contrast adjusted: and in the logarithmic domain, adding the gray value of each pixel point of the accurate edge map with the gray value of the corresponding pixel point in the illumination map after the contrast adjustment to obtain a gray map with enhanced brightness on the logarithmic domain, calculating and outputting an enhanced color image according to the enhanced gray map, shooting by using a starlight level low-illumination 200W high definition, and carrying out auxiliary shooting by using an electronic red point and a dividing line, wherein AI intelligent identification tracking is arranged for carrying out auxiliary shooting.
In summary, according to the low-illumination high-definition image processing method, the rough edge map after repair is refined, and the obtaining of the accurate edge map includes: initializing all pixel points of the I' edge to be 0, and reassigning the pixel points by adopting the following method:
1) If Iedge (x, y) is 0 and Iedge (x+1, y) is 1, then Iedge' (x+M, y) is 1;
2) If Iedge (x, y) is 0 and Iedge (x, y+1) is 1, then I' edge (x, y+M) is 1;
wherein, (x, y) is the current pixel point, M represents half width or half height of the template used for repairing the edge map, iedge represents the rough edge map after repairing, and I' edge represents the accurate edge map.
It is noted that relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, 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 one … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
Although embodiments of the present invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made therein without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (8)
1. A low-illuminance high-definition image processing method, characterized in that the method comprises the steps of:
1) Respectively solving a bright channel image and a dark channel image of the low-illumination image by using a bright channel prior and a dark channel prior;
2) Obtaining a self-adaptive atmospheric illumination map through the bright channel image;
3) Obtaining a self-adaptive transfer function diagram through the dark channel image and the self-adaptive atmospheric illumination diagram;
4) Restoring a scene image according to the low-illumination image, the self-adaptive atmospheric illumination map and the self-adaptive transfer function map in the atmospheric scattering physical model, wherein the restored scene image is determined according to the following expression:
J(x)＝I(x)-A(x)A(x)(max(t(x),t0))+1；
wherein x represents two-dimensional space coordinates, J (x) is a restored scene image, I (x) is a low-illumination image, A (x) is an adaptive atmospheric illumination map, t (x) is an adaptive transfer function map, and t0 has a value of 0.1.
2. The method for processing a low-illumination high-definition image according to claim 1, wherein in step 1), the specific method for respectively obtaining the bright channel image and the dark channel image of the low-illumination image by using the bright channel prior and the dark channel prior is as follows:
and (3) obtaining a bright channel image of the low-illumination image by using the bright channel prior:
when the low-illumination image is a gray image, the gray low-illumination image is used as a guide image of a GuidedFilter filter;
the guide image is determined according to the following expression:
Iguide(x)＝I(x)；
wherein Iguide (x) is a guide image, and I (x) is a gray-scale low-illumination image;
performing maximum filtering on the obtained guide image to obtain a rough extracted bright channel image;
the coarsely extracted bright channel image is determined according to the following expression:
Ilig(x)＝maxx∈Ω(x)(Iguide(x))；
wherein Ilig (x) is a rough extracted bright channel image, x is a two-dimensional space coordinate, and Ω (x) is a square neighborhood centered on the coordinate x;
when the low-illumination image is a color image, calculating the maximum value of R, G, B color channels at each pixel point of the color low-illumination image as a guide image of a GuidedFilter filter;
the guide image is determined according to the following expression:
Iguide(x)＝maxc∈{R,G,B}(Ic(x))；
wherein Iguide (x) is a guide image, c is a color channel, c E { R, G, B } are R, G, B color channels, and Ic is a color channel of a color low-illumination image;
performing maximum filtering on the obtained guide image to obtain a rough extracted bright channel image;
the coarsely extracted bright channel image is determined according to the following expression:
Ilig(x)＝maxx∈Ω(x)(Iguide(x))；
wherein Ilig (x) is a rough extracted bright channel image, x is a two-dimensional space coordinate, and Ω (x) is a square neighborhood centered on the coordinate x;
and (3) carrying out edge-preserving smooth filtering on the rough extracted bright channel image through a GuidedFilter filter by utilizing the guide image, and finally obtaining a refined bright channel image Ilight (x).
3. The method for processing a low-illuminance high-definition image according to claim 1, wherein in step 2), the specific method for obtaining the adaptive atmospheric illumination map from the bright channel image is as follows:
obtaining a self-adaptive atmospheric illumination map by utilizing the bright channel image;
the adaptive atmospheric illumination map is determined according to the following expression:
ilight (x) =A (x) t (x) +A (x) (1-t (x)) is: a (x) =ilight (x);
wherein Ilight (x) is a thinned bright channel image, A (x) is a self-adaptive atmospheric illumination map, and t (x) is a self-adaptive transfer function map.
4. A low-luminance high-definition image processing method according to claim 1, wherein in step 3),
the specific method for obtaining the self-adaptive transfer function diagram through the dark channel image and the self-adaptive atmospheric illumination diagram comprises the following steps:
obtaining an adaptive transfer function diagram by using the dark channel image and the adaptive atmospheric illumination diagram;
the adaptive transfer function map is determined according to the following expression:
idark (x) =A (x) (1-t (x)), namely: t (x) =1-widmark (x) a (x);
wherein t (x) is an adaptive transfer function diagram, w is a correction factor, and 0 < w is less than or equal to 1, so as to reserve a small part of dark area and increase the depth perception of a scene, and w=0.95 is taken here.
5. The method for processing a low-illumination high-definition image according to claim 1, wherein in step 4), the specific method for restoring the scene image according to the low-illumination image, the adaptive atmospheric illumination map and the adaptive transfer function map in the atmospheric scattering physical model is as follows: restoring the scene image through the atmospheric scattering physical model by utilizing the low-illumination image, the self-adaptive atmospheric illumination map and the self-adaptive transfer function map;
the restored scene image is determined according to the following expression:
J(x)＝I(x)-A(x)A(x)(max(t(x),t0))+1；
wherein J (x) is a restored scene image, I (x) is a low-illumination image, A (x) is an adaptive atmospheric illumination image, t (x) is an adaptive transfer function image, and t0 has a value of 0.1, so as to avoid that the scene image J (x) contains too much noise when t0 tends to 0
And outputting the formed image through the Wifi module.
6. A low-illuminance high-definition image processing method according to claim 1, characterized in that the method comprises the steps of:
calculating a gray scale map of the input original image;
calculating an accurate edge map of the gray map: calculating gradient amplitude values of the bright pixel points and the dark pixel points of the gray level map by adopting different edge detection operators respectively to obtain a rough edge map; denoising, repairing and refining the rough edge map to obtain an accurate edge map;
calculating an illumination map according to the gray level map and the accurate edge map: subtracting the gray value of the corresponding pixel point in the accurate edge map from the gray value of each pixel point of the gray map in the logarithmic domain to obtain an illumination map in the logarithmic domain;
adjusting the contrast of the illumination map;
synthesizing an enhanced gray scale image according to the accurate edge image and the illumination image with adjusted contrast: in the logarithmic domain, adding the gray value of each pixel point of the accurate edge map with the gray value of the corresponding pixel point in the illumination map after the contrast adjustment to obtain a gray map with enhanced brightness in the logarithmic domain;
and calculating and outputting the enhanced color image according to the enhanced gray level image.
7. The low-illuminance high-definition image processing method according to claim 1, wherein:
refining the rough edge map after repair to obtain a precise edge map, including:
initializing all pixel points of the I' edge to be 0;
the pixel points are reassigned by adopting the following method:
1) If Iedge (x, y) is 0 and Iedge (x+1, y) is 1, then Iedge' (x+M, y) is 1;
2) If Iedge (x, y) is 0 and Iedge (x, y+1) is 1, then I' edge (x, y+M) is 1.
8. The method of claim 7, wherein (x, y) is a current pixel, M is a half width or half height of a template used for repairing the edge map, iedge is a rough edge map after repairing, and I' edge is a precise edge map.
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| CN117635506A (en) * | 2024-01-24 | 2024-03-01 | 成都航天凯特机电科技有限公司 | Image enhancement method and device based on AI-energized Mean Shift algorithm |
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| CN117635506B (en) * | 2024-01-24 | 2024-04-05 | 成都航天凯特机电科技有限公司 | Image enhancement method and device based on AI-energized Mean Shift algorithm |
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