Infrared image de-noising based on K-SVD over-complete dictionaries learning

The sparse representation of image based on over-complete dictionaries is a new image representation theory. Using the redundancy of over-complete dictionaries can effectively capture the various structure detail characteristics of an image, so as to realize the efficient representation of the image. In this paper we propose an infrared image de-noising algorithm based on K-SVD over-complete dictionaries learning using the over-complete dictionary image sparse representation theory. The experimental results compared with the common de-noising algorithm processing results prove the effectiveness of the proposed method.