Title :
A novel image denoising method based on DCT basis and sparse representation
Author :
Fen, Zhang ; Kai, Xie
Author_Institution :
Coll. of Inf. & Mech. Eng., Beijing Inst. of Graphic Commun., Beijing, China
Abstract :
Image denoising plays an important role in the image pre-processing. There are many methods to solve the problem of image denoising. In this paper, we will propose a new method which based on the K-SVD algorithm by learning dictionary from the noisy image itself. From this Over-complete dictionary, we can describe the image´s content effectively. Combine with the sparse representation coefficients which we can get from the pursuit algorithm, we can get the denoised image at last. Experiments result shows that: compared with other methods of image denoising, our method gets a superior result.
Keywords :
discrete cosine transforms; image denoising; image representation; singular value decomposition; DCT basis; K-SVD algorithm; dictionary learning; image denoising method; image preprocessing; over-complete dictionary; sparse representation; Noise reduction; K-SVD method; Over-complete dictionary; image denoising; sparse representation;
Conference_Titel :
Cross Strait Quad-Regional Radio Science and Wireless Technology Conference (CSQRWC), 2011
Conference_Location :
Harbin
Print_ISBN :
978-1-4244-9792-8
DOI :
10.1109/CSQRWC.2011.6037203