Image denoising method based on Treelet transformation and minimum mean-square error estimation
A minimum mean square error and image technology, applied in the field of image processing, can solve problems such as inaccurate similarity weights and high computational complexity
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[0053] Attached below figure 1 The steps of the present invention are further described in detail.
[0054] Step 1, input an image to be denoised.
[0055] Step 2, search for similar image blocks.
[0056] 2a) Select the central image patch and search window.
[0057] For the input noisy image X, take any pixel as the center, take 5-11 pixels as the side length, and take a square area as the center image block. In the embodiment of the present invention, a central pixel block with a size of 7×7 is selected. With 21-41 pixels as the side length, determine a square search window. In the embodiment of the present invention, a search window with a size of 39×39 is selected.
[0058] 2b) Select image blocks. All image blocks of the same size as the central image block are selected by scanning line by line in the search window.
[0059] 2c) Select similar image blocks
[0060] Calculate the similarity between the central image block in step 2a) and the image block selected in ...
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