A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Theory for Multiresolution Signal Decomposition: The Wavelet Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Ten lectures on wavelets
Characterization of Signals from Multiscale Edges
IEEE Transactions on Pattern Analysis and Machine Intelligence
Wavelets and subband coding
Techniques and standards for image, video, and audio coding
Techniques and standards for image, video, and audio coding
Digital Image Processing
De-noising by soft-thresholding
IEEE Transactions on Information Theory
Projection-based spatially adaptive reconstruction of block-transform compressed images
IEEE Transactions on Image Processing
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We propose a technique for image enhancement, especially for denoising and deblocking based on wavelets. In this proposed algorithm, a frame wavelet system designed as an optimal edge detector is used. And our theory depends on Lipschitz regularity, spatial correlation, and some important assumptions. The performance of the proposed algorithm is tested on three popular test images in image processing area. Experimental results show that the performance of the proposed algorithm is better than those of other previous denoising techniques like spatial averaging filter, Gaussian filter, median filter, Wiener filter, and some other wavelet based filters in the aspect of both PSNR and human visual system. The experimental results also show that our algorithm has approximately same capability of deblocking as those of previous developed techniques.