Vision is the most important source of information for humans and the acquisition of images has numerous applications in science, engineering, medicine and also in consumer devices such as cameras, mobile phones, etc. Digital image acquisition, in particular, has become the most common means of producing images; it has almost fully replaced image acquisition on ...lm. A typical digital acquisit...

In this paper we introduce a dataset of uncompressed color images taken with three digital cameras and exhibiting different levels of natural noise due to low-light conditions. For each scene there are on average two low-noise and two high noise images that are aligned at the pixel level both spatially and in intensity. The dataset contains over 100 scenes and more than 400 images, including bo...

This article presents a detailed implementation of the Non-Local Bayes (NL-Bayes) image denoising algorithm. In a nutshell, NL-Bayes is an improved variant of NL-means. In the NLmeans algorithm, each patch is replaced by a weighted mean of the most similar patches present in a neighborhood. Images being mostly self-similar, such instances of similar patches are generally found, and averaging th...

Scanning transmission electron microscopy (STEM) provides sub-ångstrom, atomic resolution images of crystalline structures. However, in many applications, the ability to extract information such as atom positions, from such electron micrographs, is severely obstructed by low signal-to-noise ratios of the acquired images resulting from necessary limitations to the electron dose. We present a den...

Spatially adaptive nonparametric regression estimation is one of the most promising recent directions in image processing. The Transforms and Spectral Techniques Research Group at the Department of Signal Processing, Tampere University of Technology, has been active in this novel …eld starting from about 2002. The results achieved with application to di¤erent image and video processing problems...

Patch-based denoising techniques have proved to be very efficient. Indeed, they account for the correlations that exist among the patches of natural images, even when degraded by noise. In this context, we propose a denoising method which tries to minimize over-smoothing of textured areas (an effect observed with NLmeans), to avoid staircase effects in monotonically varying areas (an effect obs...