Hyperspectral data lossy compression has not yet achieved global acceptance in the remote
sensing community, mainly because it is generally perceived that using compressed images …

The availability of massive amounts of data in histopathological whole-slide images (WSIs)
has enabled the application of deep learning models and especially convolutional neural …

Scanning orders of bitplane image coding engines are commonly envisaged from
theoretical or experimental insights and assessed in practice in terms of coding …

Image coding systems have been traditionally tailored for multiple instruction, multiple data
(MIMD) computing. In general, they partition the (transformed) image in codeblocks that can …

This paper introduces a probability model for symbols emitted by bitplane image coding
engines, which is conceived from a precise characterization of the signal produced by a …

This paper describes a low-complexity, high-efficiency, lossy-to-lossless 3D image coding
system. The proposed system is based on a novel probability model for the symbols that are …

Modern image and video compression standards employ computationally intensive
algorithms that provide advanced features to the coding system. Current standards often …

Entropy is a measure of a message uncertainty. Among others aspects, it serves to
determine the minimum coding rate that practical systems may attain. This paper defines an …

The JPEG2000 system provides scalability with respect to quality, resolution and color
component in the transfer of images. However, scalability with respect to semantic content is …

Purpose: Automation of organ segmentation, via convolutional neural networks (CNNs), is
key to facilitate the work of medical practitioners by ensuring that the adequate radiation …