Noise reduction method after histogram equalization of low-illumination image
An image histogram and low-illumination technology, applied in image enhancement, image data processing, instruments, etc., can solve problems such as cross-border, image blur, poor effect, etc., to improve the effect of noise reduction and reduce the risk of instability Effect
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[0030] The present invention will be further explained below in conjunction with the accompanying drawings.
[0031] The standard histogram equalization method includes the following steps:
[0032] 1. Traverse the entire image and count the number of pixels corresponding to each gray value;
[0033] 2. Calculate the probability of the number of pixels in each gray value PMF=corresponding number of pixels / total pixels;
[0034] 3. According to the gray value from small to large, calculate the cumulative probability CDF of each gray value = less than or equal to the sum of the probability of this gray value;
[0035] 4. Calculate the new gray value of each gray value after mapping = cumulative probability * maximum brightness * original gray value, and then round up.
[0036] Such as figure 1 Shown is the pixel brightness distribution of a typical low-light image at night, such as figure 2 It shows the brightness distribution of pixels after standard histogram equalization...
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