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Image enhancement method and image enhancement device
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An image enhancement, image technology, applied in the field of image processing, can solve the problem of insufficient contrast of local detail information
Active Publication Date: 2012-11-21
CHERY AUTOMOBILE CO LTD
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In fact, since algorithms such as SSR and MSR all assume that the light is evenly distributed in space, this leads to the global brightness approaching the mean value, which makes the contrast of local detail information insufficient.
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Embodiment 1
[0060] This embodiment provides an image enhancement method, comprising the following steps:
[0061] S101 The gray value of the pixel whose coordinates are (x, y) in the current image is I(x, y), perform multi-scale Retinex algorithmprocessing on I(x, y), and then perform EXP transformation to obtain R Y (x,y);
[0062] S102 through the gain compensation method for R Y (x,y) is corrected to get R' M (x,y), where R' of the pixels in the selected area M The average value of (x,y) is I m ;
[0063] S103 through the nonlinear S-curve transfer function to R' M (x,y) for mapping, where the S-curve transfer function is:
[0064] I out ( x , y ) = D × R M ′ ( x , y ...
Embodiment 2
[0068] Such as Figure 4 As shown, the present embodiment provides an image enhancement method, which is preferably used for infrared images, especially for vehicle-mounted night visioninfrared images, comprising the following steps:
[0069] S201, use the brightness adjustment function to perform global brightness adjustment on the gray value I(x, y) of the pixel whose coordinates are (x, y) in the current image to obtain I A (x,y), where the global brightness adjustment function is as follows:
[0070] I A ( x , y ) = w L × log [ I ( x , y ) ...
Embodiment 3
[0120] This embodiment provides an image weakening device, including:
[0121] The multi-scale Retinex processing unit is used to perform multi-scale Retinex algorithm processing on the gray value of the pixel whose coordinates are (x, y) in the current image (x, y), and then perform EXP transformation to obtain R Y (x,y);
[0122] Gain compensation unit for adjusting R by gain compensation method Y (x,y) is corrected to get R' M (x,y), where R' of the pixels in the selected area M The average value of (x,y) is I m ;
[0123] Non-linear S-curve transfer function mapping unit for R' by nonlinear S-curve transfer function M (x,y) for mapping, where the S-curve transfer function is:
[0124] I out ( x , y ) = D × R M ′ ( ...
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Abstract
The invention provides an image enhancement method and an image enhancement device. The method comprises the following steps: (1), performing multiscale Retinex algorithm treatment on a gray value of a pixel in a current image, and then obtaining RY(x, y) after EXP conversion; (2), revising RY (x, y) by a gain compensation method to obtain R'M (x, y), wherein the average value of the R'M (x, y) of the pixel in a selected area is Im; and (3) mapping the R'M (x, y) by a non-linear S-curve transfer function, wherein the coefficients (a and b) in the S-curve transfer function are parameters changing with the Im, a represents the increment speed of an S-curve, and b represents the position of the S-curve. The image enhancement method and the image enhancement device can not only enhance the contrast ratio of the overall brightness of the image, but also reduce the degree of the overall brightness toward to the average value easily resulted from algorithms like SSR (Single-Scale Retinex) and MSR (Multi-Scale Retinex) and the like, so that the contrast ratio of the local detail information is enhanced.
Description
technical field [0001] The invention belongs to the field of image processing, and in particular relates to an image enhancement method and device. Background technique [0002] About 75% of the information people get from the outside world comes from video images. However, when the camera is shooting, due to insufficient night light conditions, heavy fog, heavy rain, sand and dust and other severe weather conditions, the images captured by the camera are often severely degraded, resulting in a decline in image quality, blurring, and low contrast. There are two types of methods for processing images degraded by severe weather using digital imageprocessing technology: image enhancement and image restoration. Image restoration refers to the process of removing or minimizing known degradations or portions of known degradations in an image. Currently, image augmentation is a more general approach. Image enhancement refers to a kind of image processing according to the requir...
Claims
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