Layered self-adaptive threshold video denoising method
An adaptive threshold and video technology, applied in the field of video denoising, can solve the problems of not making good use of transform domain coefficients, direction information, not making good use of Surfacelet, and advanced hardware
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[0058] Below in conjunction with accompanying drawing, technical scheme of the present invention is described in further detail:
[0059] A hierarchical adaptive threshold video denoising method, such as figure 1 shown, including the following steps:
[0060] Step 1, input the noisy video, and perform Surfacelet transformation on the noisy video, and decompose it into 4 layers;
[0061] Step 2, use the median estimation method to estimate the standard deviation of the highest-layer directional subband noise in the Surfacelet transform domain:
[0062] σ 1 =median(|y(i,j,k)|) / 0.6745
[0063] In the formula, y(i,j,k) is a certain direction subband of the highest layer Surfacelet transform domain; i∈{1,2,3,…,I}, j∈{1,2,3,…,J} , k∈{1,2,3,…,K}; I, J, K are the length, width, and height of the sub-band respectively; apply the Monte Carlo algorithm to estimate the standard deviation of each layer of Gaussian white noise after Surfacelet transformation relation:
[0064] ...
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