NOISE

Complex wavelet joint denoising and demosaicing using Gaussian scale mixtures

Wavelet-based demosaicing techniques have the advantage of being computationally relatively fast, while having a reconstruction performance that is similar to state-of-the-art techniques. Because the demosaicing rules are linear, it is fairly simple …

Segmentation of brain blood vessels using projections in 3-D CT angiography images

Segmenting cerebral blood vessels is of great importance in diagnostic and clinical applications, especially in quantitative diagnostics and surgery on aneurysms and arteriovenous malformations (AVM). Segmentation of CT angiography images requires …

Split-Bregman-based sparse-view CT reconstruction

Total variation minimization has been extensively researched for image denoising and sparse view reconstruction. These methods show superior denoising performance for simple images with little texture, but result in texture information loss when …

A GPU-accelerated real-time NLMeans algorithm for denoising color video sequences

Abstract. The NLMeans filter, originally proposed by Buades et al., is a very popular filter for the removal of white Gaussian noise, due to its simplicity and excellent performance. The strength of this filter lies in exploiting the repetitive …

Wavelet-based denoising for 3D OCT images

Optical coherence tomography produces high resolution medical images based on spatial and temporal coherence of the optical waves backscattered from the scanned tissue. However, the same coherence introduces speckle noise as well; this degrades the …

Estimating the probability of the presence of a signal of interest in multiresolution single- and multiband image denoising

We develop three novel wavelet domain denoising methods for subband-adaptive, spatially-adaptive and multivalued image denoising. The core of our approach is the estimation of the probability that a given coefficient contains a significant noise-free …