Regional exposure algorithm based on weighted gray entropy difference
A gray entropy, sub-region technology, applied in the field of image processing, can solve problems such as information loss and inability to adjust, and achieve the effect of improving image quality, improving adaptability, and enhancing scene and local details
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[0041] Embodiments of the present invention are described in further detail below in conjunction with the accompanying drawings:
[0042] The regional exposure algorithm (REABW) based on the weighted gray entropy difference includes the following steps:
[0043] Step 1: In a fixed scene, calculate the weighted gray entropy difference U at each exposure time, and obtain the mapping relationship between the weighted gray entropy difference and the exposure time.
[0044] In this step, the formula for calculating the weighted gray entropy difference is as follows:
[0045]
[0046] G=|G mean -G median |
[0047] Among them, U is the weighted gray entropy difference, E is the information entropy, G is the gray offset, and G mean is the average gray value, G mean is the gray level median, d is the image depth, and the α weight value is set to 0.5. The exposure time is 25, 50, 75, 100, 125, 150, 175, 200, 225, 250, the unit is ms, such as figure 1 shown.
[0048] Step 2: ...
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