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Image denoisig is becoming an essential step for analysis of images which occurs due to the imperfections of sensors or during the transmission of data. A novel algorithm for image denoising is proposed, based on fuzzy logics. Using fuzzy features an algorithm is primed which adaptively removes impulse noises. This algorithm consists of two parts including the detection of noise and the removal of...
Magnitude-only resting-state fMRI data have been largely investigated via independent component analysis (ICA) for exacting spatial maps (SMs) and time courses. However, the native complex-valued fMRI data have rarely been studied. Motivated by the significant improvements achieved by ICA of complex-valued task fMRI data than magnitude-only task fMRI data, we present an efficient method for de-noising...
This paper presents results of our study intended on analysis of visual quality of different types of images subject to denoising. More than 100 experiments with observers have been carried out to assess visual quality of denoised images. Two filters — standard DCT in sliding blocks and known BM3D filter — are considered. The latter filter often provides better visual quality but not sufficiently...
Video noise reduction based on temporal spatial recursive filter isproposed in this paper. In the proposed model the recursive time-weighted average is applied to the areas where the motion has notbeen detected. The new model is able to be adaptive in each areadepending on whether the area is static or movable. More precisely, more noise removal will be done in the static areas, and lessremoval in...
We propose a fast, local denoising method where the Euclidean curvature of the noisy image is approximated in a regularizing manner and a clean image is reconstructed from this smoothed curvature. User preference tests show that when denoising real photographs with actual noise our method produces results with the same visual quality as the more sophisticated, nonlocal algorithms Non-local Means and...
Visual restoration and recognition are traditionally addressed in pipeline fashion, i.e. denoising followed by classification. Instead, observing correlations between the two tasks, for example clearer image will lead to better categorization and vice visa, we propose a joint framework for visual restoration and recognition for handwritten images, inspired by advances in deep autoencoder and multi-modality...
Image denoising is an issue in image processing, constantly spawning ideas to better deal with this problem. Both the Fourier and Wavelet domains remove noise, but have their own weaknesses. A hybrid Fourier-Wavelet Neighborhood Coefficient method is proposed, with experiments showing that the effectiveness of this method is greater than the previous hybrid Fourier-Wavelet neighborhood approach.
This paper aims to improve the quality of images in low light conditions. After nonlinear intensity stretching, the enlarged mixed noise is reduced using a newly proposed low rank denoising algorithm. By similar patch stacking, the established noisy matrices are assumed to be composed of low-rank noise free image, sparse random impulse noise and zero-mean Gaussian noise. Minimizing the rank of the...
This paper embeds SSIM in place of the L2 norm in a one step Non Local Means (NLM) scheme. This is possible thanks to a new form of SSIM that can be formally derived from the classical SSIM using the spreading error analysis. This approach has several advantages over L2 norm based NLM such as greater robustness to parameters setting, higher performance in terms of PSNR and SSIM, optimal subjective...
User-provided image tags are usually incomplete or noisy to describe the visual content of corresponding images. In this paper, we consider defective tagging which covers both incomplete and noisy situations, and address the problem of tag completion where tag assignments of training images are defective. While previous studies on tag completion usually assign equal penalty to empirical loss when...
As one of the best image denoising methods, the Non-Local Means(NL-Means)algorithm[5] proposed by Buades et al. generates state-of-the-art performance. However, due to the high computational complexity, it is difficult to be directly used in practical applications. In this paper, a novel fast algorithm based on the similarity of spatially sampled pixels is introduced. Compared with other fast approaches,...
The artifacts of ECG signals include baseline wander (BW), muscle (EMG) artifact, electrode motion artifact and power line interference. In order to get the optimal and robust de-noising algorithm among the generally used de-noising methods based on stationary wavelet transform (SWT), we adjust the signal-to-noise ratio (SNR) of the noisy signal from 1 db to 10 db, and evaluate the results by means...
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