A Non-Local Mean Image Denoising Method Based on Filtering Window and Parameter Adaptation
A non-local mean and self-adaptive technology, applied in image enhancement, image data processing, instrumentation, etc., can solve image noise, interference and other problems, achieve the effect of improving the quality of denoising and avoiding excessive blur
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[0046] The embodiments of the present invention will be described in detail below in conjunction with the drawings. This embodiment is implemented on the premise of the technical solution of the present invention, and provides detailed implementation and specific operation procedures, but the protection scope of the present invention is not limited to the following embodiments.
[0047] Such as figure 1 As shown, the algorithm flow of this embodiment is divided into five steps: noise detection, establishment of noise calibration matrix, determination of reference point window, determination of reference point filtering parameters, and weighting operation.
[0048] Step 1: Noise detection. First input the image. In this embodiment, an 8-bit grayscale image peppers is selected to implement the denoising method of the present invention. The size is 512×512 pixels and the resolution is 96×96 DPI, such as figure 2 (a) Shown. Add Gaussian zero-mean noise with standard deviations of 18...
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