A constrained optimization type of numerical algorithm for removing noise from images is presented. The total variation of the image is minimized subject to constraints involving the statistics of the noise. The constraints are imposed using Lagrange multipliers. The solution is obtained using the gradient-projection method. This amounts to solving a time dependent partial differential equation...

The classical solution to the noise removal problem is the Wiener filter, which utilizes the second-order statistics of the Fourier decomposition. Subband decompositions of natural images have significantly non-Gaussian higher-order point statistics; these statistics capture image properties that elude Fourier-based techniques. We develop a Bayesian estimator that is a natural extension of the ...

Several areas like remote sensing, biomedical analysis, and computer vision require good image contrast and details for better interpretations and diagnosis's. In the literature various image enhancement algorithms have been proposed to improve the perceptual aspects of the image for poorly contrasted images. The perceptual appearance of an image may be significantly improved by modifying the h...

Cellular Automata (CA) are a type of complex systems based on simple and uniformly interconnected cells. They provide an excellent method to perform complex computations in a simple way. CA can be used in image processing, because of the simplicity of mapping a digital image to a cellular automata and the ability of applying different image processing operations in real time. Noise removal is c...

Marginal noise is a common phenomenon in document analysis which results from the scanning of thick documents or skew documents. It usually appears in the front of a large and dark region around the margin of document images. Marginal noise might cover meaningful document objects, such as text, graphics and forms. The overlapping of marginal noise with meaningful objects makes it di5cult to per...

Sparse approximation has shown to be a significant tool in improving image restoration quality, assuming that the targeted images can be approximately sparse under some transform operators. However, it is impossible for a fixed system to be always optimal for all the images. In this paper, we present an adaptive wavelet tight frame technology for sparse representation of an image with multiplic...

Pushing scientific echo sounders to the limit involves the consideration of ‘‘noise’’, which is inherently frequency dependent and which also depends on bottom depth. Here, noise is quantified by measurement with a standard echo sounder, the SIMRAD EK500, at 18, 38, 120 and 200 kHz. The use of empirical relationships of noise as a function of range to reduce echo integration is described in gen...

The bioelectric potentials associated with muscle activity constitute the Electromyogram, abbreviated as EMG. These potentials may be measured at the surface of the body near a muscle of interest or directly from the muscle by penetrating the skin with needle electrodes. Since most EMG measurements are intended to obtain an indication of the amount of activity of a given muscle, or group of mus...

A parallel algorithm for reducing impulse noise from color images is proposed. The algorithm is based on a fuzzy metric and is performed in two steps followed by noise filtering using the vector median filter. An implementation of the algorithm on multi-core interface using the Open MultiProcessing (OpenMP) is presented. A performance analysis with large images is conducted. Performance is eval...