Preprocessing an image is an important element of image processing. When images are corrupted with fixed-value impulse noise or random-value impulse noise, it is essential to restore the quality of the degraded image using linear or non-linear filters, in order to make them suitable for subsequent processing. It has been proved that non-linear filters are effective in suppressing or eliminating...

One of the most important challenging factors in medical images is nominated as noise. Image denoising refers to the improvement of a digital medical image that has been infected by Additive White Gaussian Noise (AWGN). The digital medical image or video can be affected by different types of noises. They are impulse noise, Poisson noise and AWGN. Computed tomography (CT) images are subjects to ...

This paper deals with impulse noise removal from color images. The proposed noise removal algorithm employs a novel approach with morphological filtering for color image denoising; that is, detection of corrupted pixels and removal of the detected noise by means of morphological filtering. With the help of computer simulation we show that the proposed algorithm can effectively remove impulse no...

We investigate Maximum Likelihood (ML) methods for blind and semi-blind estimation of multiple FIR channels. Two blind Deterministic ML (DML) strategies are presented. In the first one, we propose to modify the Iterative Quadratic ML (IQML) algorithm in order to ”denoise” it and hence obtain consistent channel estimates. The second strategy, called Pseudo-Quadratic ML (PQML), is naturally asymp...

This paper describes a new method for design of linear phase finite impulse response (FIR) filters. This new approach, based on the ε-insensitive loss function, allows the design process to take into account not only constraints specified in the frequency domain, but also constraints on the output, time domain, signal. The performances of the proposed approach are shortly illustrated with a des...

In this paper, we propose to use a class of filters based on fractional lower order statistics (FLOS) for still image restoration in the presence of α-stable noise. For this purpose, we present a family of 2-D finite-impulse response (FIR) adaptive filters optimized by the least mean lp-norm (LMP) algorithm. Experiments performed on natural images prove that the proposed algorithms provide supe...