A 4-quadrant curvelet transform for denoising digital images
International Journal of Automation and Computing
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A new method to remove noise form image is described in the article. Curvelet transform that combines both WindowShrink and BayesShrink can be used to complete the processing. Though the Wavelet transform can do the job well, it has low Resolving rate in high frequency area and it also lacks of the direction in dealing with images. Curvelet transform have an efficient way of representing the line and surface property of image. If the WindowShrink theory and BayesShrink theory are combined, the results are better. Firstly, the image should be done by Curvelet transform, then, the noise should be declined basing on Wavelet theory and the combination of WindowShrink and BayesShrink. The results of the method described in the article are better from both PSNR and the disposed image.