During the past several years, as one of the most successful applications of sparse coding
and dictionary learning, dictionary-based face recognition has received significant attention …

Sparse representations have been extended to deal with color images composed of three
channels. A review of dictionary-learning-based sparse representations for color images is …

With the increasing use of surveillance cameras, face recognition is being studied by many
researchers for security purposes. Although high accuracy has been achieved for frontal …

In this paper, a clustering method using dictionary learning is proposed to group large
medical databases. An approach grouping similar images into clusters that are sparsely …

In compressed sensing the matrices that satisfy the Restricted Isometry Property (RIP) play
an important role. To date, however, very few results for designing such matrices are …

This book provides a broader introduction to the theories and applications of sparse coding
techniques in computer vision research. It introduces sparse coding in the context of …

In this paper, we propose a cross-range scaling technique for inverse synthetic aperture
radar (ISAR) images, by estimating the rotation velocity (RV) of a target. In the proposed …

Melanoma is the deadliest type of human skin cancer. However, it is curable if diagnosed in
an early stage. Recently, computer aided diagnosis (CAD) systems have drawn much …

In this paper novel multiple vector representations of images are proposed and a robust
dictionary learning method is designed. The multiple vector representation scheme enables …

While recent techniques for discriminative dictionary learning have demonstrated
tremendous success in image analysis applications, their performance is often limited by the …