The first part of this paper proposes an adaptive, data-driven threshold for image denoising
via wavelet soft-thresholding. The threshold is derived in a Bayesian framework, and the …

In this research, we propose to utilize the newly introduced Multi-population differential
evolution-assisted Harris Hawks Optimization Algorithm (CMDHHO) in the optimization …

A discrete denoising algorithm estimates the input sequence to a discrete memoryless
channel (DMC) based on the observation of the entire output sequence. For the case in …

A novel technique for despeckling the medical ultrasound images using lossy compression
is presented. The logarithm of the input image is first transformed to the multiscale wavelet …

Image compression is one of the most important research areas in the field of image
processing due to its large number of applications such as aerial surveillance …

Let X=(X/sub 1/,...) be a stationary ergodic finite-alphabet source, X/sup n/denote its first n
symbols, and Y/sup n/be the codeword assigned to X/sup n/by a lossy source code. The …

Our proof relies on a key idea from ergodic theory, namely the concept of B-process; this
furnishes the 'regularity condition'on stationary ergodic processes mentioned earlier. We …

The need for image enhancement and restoration is encountered in many practical
applications. For instance, distortion due to additive white Gaussian noise (AWGN) can be …

Ultrasonography has been considered as one of the most powerful techniques for imaging
organs and soft tissue structures in the human body. The main disadvantage of medical …

Image denoising is a common procedure in digital image processing aiming at the removal
of noise which may corrupt an image during its acquisition or transmission while sustaining …