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An image contrast and image gradient technology, which is applied in image enhancement, image data processing, instruments, etc., can solve the problems of robustness, lack of enhancement effect of halo phenomenon, lack of details of image enhancement algorithm, etc., and achieve noise suppression and enhancement effect Good, good enhancement, clear image details
Inactive Publication Date: 2015-06-10
UNIV OF ELECTRONICS SCI & TECH OF CHINA
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[0004] The purpose of the present invention is to provide an image contrast enhancement method based on the critical visible deviation enhancement function, which combines the critical visible deviation JND conforming to the human visual system with the image gradient field, designs enhancement and companding functions, and realizes image enhancement. method to solve the problems of lack of detail, halo phenomenon and lack of robustness of enhancement effect in existing image enhancement algorithms
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Embodiment 1
[0039] Embodiment 1: Take the underexposed image actually taken as an example:
[0040] In this embodiment, an image that is actually shot with a dark picture due to underexposure is taken as an example, as shown in Figure 3a As shown, the image resolution is 640*480 (pixels); the adjustable parameter α of the enhancement function is 0.3.
[0041] The specific implementation process of this embodiment is as follows:
[0042] Step 101. Read the R, G, and B three color component images of the original image I (x, y), and perform steps 102 to 110 for each component, corresponding to the pixel at (320, 240) in the image , and its R, G, B three component values are I R (320,240)=25, I G (320,240)=30, I B (320,240) = 34;
[0043] Step 102. Find the gradient ▽ I(x, y) of the image I(x, y), and approximate it with the first-order forward difference:
[0044] ▽I(x,y)≈(I(x+1,y)-I(x,y),I(x,y+1)-I(x,y));
[0045] At this time, the gradient values in the x direction and y direc...
Embodiment 2
[0068] Embodiment 2: Take the actual strong backlight image taken as an example:
[0069] This embodiment selects the actual strong backlight image taken as an example, such as Figure 4a As shown, the image resolution is 512*512 (pixels), and the operation steps are completely the same as those in Embodiment 1, and will not be repeated here.
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Abstract
The invention discloses an image contrast enhancing method. The image contrast enhancing method comprises the following steps: designing a critical visual deviation enhancing function and a gradient companding function by utilizing critical visual deviation characteristics of human eye vision, and reconstructing an enhanced image from the enhanced gradient field. The image contrast enhancing method specifically comprises the following steps: firstly, calculating an original image gradient field and obtaining a critical visual deviation threshold value and a critical visual deviation enhancing function according to the average image background brightness; performing gradient companding of different degrees according to different gradient amplitude values; finally, processing by adopting the gradient field reconstructing method and linear stretching process to obtain the output image. The image contrast enhancing method disclosed by the invention is good in noise restraining and enhancing effect, clear in detail, and meets the human eye vision characteristics better; the enhanced image of the same image is repeatedly enhanced by many times, so that the enhanced image is stable in quality. Meanwhile, for the image with relatively good quality, the image is not worsened in quality after being enhanced through the method.
Description
technical field [0001] The invention belongs to the technical field of image enhancement, and in particular relates to an image contrast enhancement method based on a critical visual deviation enhancement function. Background technique [0002] Image enhancement technology is a kind of image processing technology, which can significantly improve image quality, make image content more layered and subjective observation effect more in line with people's needs. In real life, there are often various problems with images, for example: when taking pictures, the aperture is too small, resulting in dark images; the contrast of the scene is low, which makes the focus of the image not prominent; overexposure causes image abnormalities, and photos are whitened. [0003] At present, the methods of image contrast enhancement mainly include: Chang-Hsing Lee et al. In the literature [Image enhancement approach using the just-noticeable-difference model of the human cisual system, Journal o...
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