In recent years, no-reference/blind image quality assessment (NR-IQA), as a fundamental
but challenging research problem, has been attracting significant attention in the field of …

Super-resolution reconstruction proposes a fusion of several low-quality images into one
higher quality result with better optical resolution. Classic super-resolution techniques …

The search for efficient image denoising methods is still a valid challenge at the crossing of
functional analysis and statistics. In spite of the sophistication of the recently proposed …

We present a nonparametric regression method for denoising 3-D image sequences
acquired via fluorescence microscopy. The proposed method exploits the redundancy of the …

Quantitative analysis of biological image data generally involves the detection of many
subresolution spots. Especially in live cell imaging, for which fluorescence microscopy is …

In this paper, we consider denoising of image sequences that are corrupted by zero-mean
additive white Gaussian noise. Relative to single image denoising techniques, denoising of …

Live fluorescence microscopy has the unique capability to probe dynamic processes, linking
molecular components and their localization with function. A key goal of microscopy is to …

A novel image sequence denoising algorithm is presented. The proposed approach takes
advantage of the self-similarity and redundancy of adjacent frames. The algorithm is inspired …

In this paper we present a new patch-based empirical Bayesian video denoising algorithm.
The method builds a Bayesian model for each group of similar space-time patches. These …

We present a novel action recognition method based on space-time locally adaptive
regression kernels and the matrix cosine similarity measure. The proposed method uses a …