We design a novel network architecture for learning discriminative image models that are employed to efficiently tackle the problem of grayscale and color image denoising. Based on the proposed architecture, we introduce two different variants. The first network involves convolutional layers as a core component, while the second one relies instead on non-local filtering layers and thus it is ab...

This paper proposes an effective color-difference-based (ECDB) interpolation algorithm for color filter array (CFA) image demosaicking. A CFA image consists of a set of spectrally selective filters which are arranged in an interleaved pattern such that only one color component is sampled at each pixel location. To improve the quality of reconstructed fullcolor images from CFA images, the ECDB a...

Sparse representations of signals have drawn considerable interest in recent years. The assumption that natural signals, such as images, admit a sparse decomposition over a redundant dictionary leads to efficient algorithms for handling such sources of data. In particular, the design of well adapted dictionaries for images has been a major challenge. The K-SVD has been recently proposed for thi...