Image noise reduction method and device
An image noise reduction, image technology, applied in the field of image processing, can solve the problem of noise reduction without color noise
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Embodiment 1
[0034] refer to Figure 1-4 .
[0035] S1, perform the binning operation on the last frame image according to the block of 16x16, obtain the Pixel average value of each block, a total of N, N=(image width / 16)*(image height / 16), store in the ram;
[0036] S2. Calculate the probability PRO0 of the current frame image Pixel in the flat area. Specifically, perform gradient calculations on the current frame image in 4 directions, take n points in the vertical gradient direction, and calculate the average value to obtain P0 and P1, and use P0 and P1 to calculate the gradient of the current direction; the gradients of the four directions take the maximum value and map to the probability map to obtain the flat area probability PRO0;
[0037] S3, perform bilateral filtering on the current frame image Pixel to obtain PIXcur; at the same time, perform interpolation on the previous frame image Binning to obtain N points to obtain PIXref, specifically, perform bilateral filtering on the c...
Embodiment 2
[0042] refer to Figure 1-4 .
[0043] In S1, the image is divided into H parts at intervals of 16 in the horizontal direction, that is, H=width / 16, and divided into V parts at intervals of 16 in the vertical direction, that is, V=height / 16. A total of N=H*V 16x16 blocks are obtained. Accumulate the PIX in each block, and divide the final accumulated value by 256 to obtain the binning operation result, namely PIX avg =Σ PIX / 256, write the obtained N points into ram.
Embodiment 3
[0045] refer to Figure 1-4 .
[0046]In S2, calculate the probability PRO0 that the Pixel of the current frame image is in the flat region, specifically, perform gradient calculations on the current frame image in four directions. The gradient calculation takes n points in the vertical gradient direction, calculates the average value, and obtains P0 and P1, and uses P0 and P1 to calculate the gradient in the current direction; for example, to calculate the gradient in the vertical direction, n is 5, and the current Pixel coordinates are (11, 8), the P0 point needs 5 points to calculate the average value, and the coordinates of the 5 points are Pix(8,6), Pix(8,7), Pix(8,8), Pix(8,9), Pix(8 , 10); P1 needs 5 points to calculate the average value, and the coordinates of 5 points are Pix(12, 6), Pix(12, 7), Pix(12, 8), Pix(12, 9), Pix(12 , 10), get the gradient |P0-P1| in the vertical direction. Calculate the gradients of the remaining 3 directions in the same way, and take th...
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