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The denoising of natural images corrupted by noise is a long established problem in signal or image processing. Noise is signal dependent and is difficult to be removed without impairing image details. Multi-resolution methods are based on image transformations that reduce image resolution and they are able to segment objects of different sizes depending on the chosen resolution. In this work the...
Bioradar echoes are often very weak and submerged in noise. The SNR of radar signal is very low. Therefore, echo signal denoising is indispensable for extracting life information. In this paper, the method of weak signal denoising based on the combination of accumulation in frequency domain and wavelet transform is proposed. First, the effectiveness of frequency domain in accumulation and wavelet...
Wave atom transform is a new multi-resolution technique, which has the ability to adapt to arbitrary local directions of a pattern, and to sparsely represent anisotropic patterns aligned with the axes. In this paper, a de-noising technique is proposed to remove the rician noise from Magnetic Resonance Images using wave atom shrinkage. It is well known that the noise in magnetic resonance imaging has...
This paper proposes a method which combines Sobel edge detection operator and soft-threshold wavelet de-noising to do edge detection on images which include White Gaussian noises. In recent years, a lot of edge detection methods are proposed. The commonly used methods which combine mean de-noising and Sobel operator or median filtering and Sobel operator can not remove salt and pepper noise very well...
Frequency estimation in passive location based on non-cooperative information sources plays an important role. And existing methods such as wavelet transform (WT) can't satisfy the precision of frequency estimation what is needed in location. In order to solve the puzzle, the Hilbert-Huang transform(HHT) is adopted in this article. HHT is based on the local characteristics of signals, which is an...
Wavelet image denoising has been one of important method of denoising for image processing in recent years. In this paper, The denoising operators used in wavelet domain based on least squares support vector machines (LS-SVM) are obtained and image denoising using proposed operators is given, based on the principle of wavelet denoising. In the experiment of image denoising, the influence of different...
In this paper a new method for digital image watermarking based on zero assigned filter banks and embedded zero tree wavelet (EZW) algorithm is presented. An image is partitioned into 128 times 128 subblocks and each block is processed in a three stage decomposition structure by a filter bank which is assigned a zero around the stop band. The coefficients to be marked are chosen according to the EZW...
There are many noise sources for images. Images are, in many cases, degraded even before they are encoded. Previously, we focused on Poisson noise (Huang, X. et al., IEEE Int. Conf. on Multimedia and Expo, vol.1, p.593, 2003). Unlike additive Gaussian noise, Poisson noise is signal-dependent and separating signal from noise is a difficult task. A wavelet-based maximum likelihood method for a Bayesian...
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