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they have different pros and cons.. should be used by what you want to get. I'll point out only cons of 2) and 3) in this post.
A) wavelet denoising the main problem of wavelet denoising is halo effects around edges. I guess because wavelet denoising hasn't edge detection calculation (need to be explained by a professional. I'm just an amateur) and if you raise the noise levels (thresholds), then edges are smoothed out.
B) anisotropic denoising there are 2 problems in this filter. one is killing dithering pixels. the gradation of the result image gets "contoured" lines. the other is about anisotropic noises. if images have noises like lined textures, the filter regard them as edges, and try to make them contour lines. but they are simply ugly :/
midzki
Caution: this post is written by my arbitrary thought. it must be corrected by a professional.
There are 3 types of useful filterings (ignoiring some useless filtering... such as dust&scratch :p).
1) contrast threshold blur (smart blur, surface blur, selective gaussian blur)
2) wavelet denoising (neat image, noise ninja, noise ware)
3) anisotropic denoising (greycstration)
they have different pros and cons.. should be used by what you want to get. I'll point out only cons of 2) and 3) in this post.
A) wavelet denoising
the main problem of wavelet denoising is halo effects around edges. I guess because wavelet denoising hasn't edge detection calculation (need to be explained by a professional. I'm just an amateur) and if you raise the noise levels (thresholds), then edges are smoothed out.
B) anisotropic denoising
there are 2 problems in this filter. one is killing dithering pixels. the gradation of the result image gets "contoured" lines.
the other is about anisotropic noises. if images have noises like lined textures, the filter regard them as edges, and try to make them contour lines. but they are simply ugly :/