A Novel Image Reconstruction Algorithm Based on Concatenated Dictionary

I mage 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 computation al efficiency. This paper presents a novel method for image reconstruction, which decomposit es the image by concatenat ing a redundant dictionary of several bases and then reconstruct the image efficiently by means of Matching Pursuit algorithm. The proposed method constructs the concatenate d dictionary with cosine bases, wavelet bases and contourlet bases , which will lead to a better approximation of the original image. The experimental results show that the proposed algorithm can greatly reduce the computation al complexity and generate a better reconstruction effect compared with previous methods .