Sparse representation and low-rank double restraints-based nonlocal denoising method
A sparse representation, non-local technology, used in image data processing, instrumentation, computing and other directions, can solve the problem of smoothness in areas that cannot be homogeneous to maintain image edge and texture details, high noise image effect is general, image signal energy is not concentrated enough, etc. problems, to achieve the effect of overcoming insufficient retention, improving adaptability, and being easy to distinguish
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[0051] The present invention will be further described below in conjunction with the accompanying drawings.
[0052] Refer to attached figure 1 , the specific steps of the method of the present invention are as follows.
[0053] Step 1, input a noise image, the size of the image is m×n pixels.
[0054] Step 2, according to the following formula, estimate the standard deviation of the noise image:
[0055] σ=c×M{a×|vec(Y*T)-M{a×vec(Y*T)}|}
[0056] Among them, σ represents the noise standard deviation of the noise image, c represents the adjustment factor of the median filter, and the value of c is 1.4186, M{} represents the median value, a represents the adjustment factor of the low-pass filter, and the value of a is |·| indicates the operation of taking the absolute value, Y indicates the noise image matrix, T indicates a low-pass filter of a 2×2 size matrix, * indicates the convolution operation, vec indicates that the noise image matrix Y is transformed in order from le...
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