A Novel Image Reconstruction Algorithm Based on Concatenated Dictionary

Image sparse representation plays a vital role in the process of image reconstruction. In recent years, several pioneering works suggested that signals/images could be represented sparsely with a redundant dictionary. The selection of components from the dictionary directly influences the precision of the reconstructed image, while the scale of dictionary influences the computational efficiency. This paper presents a novel method for image reconstruction, which decomposites the image by concatenating a redundant dictionary of several bases