TY - GEN
T1 - Impulsive noise removal from images using sparse representation and optimization methods
AU - Beygi-Harchegani, Sajjad
AU - Kafashan, Mohammadmehdi
AU - Marvasti, Farokh
PY - 2010
Y1 - 2010
N2 - In this paper, we propose a new method for impulsive noise removal from images. It uses the sparsity of natural images when they are expanded by mean of a good learned dictionary. The zeros in sparse domain give us an idea to reconstruct the pixels that are corrupted by random-value impulse noises. This idea comes from this reality that noisy image in sparse domain of original image will not have a sparse representation as much as original image sparsity. In this method we assume that the proper dictionary to achieve image in sparse domain is available.
AB - In this paper, we propose a new method for impulsive noise removal from images. It uses the sparsity of natural images when they are expanded by mean of a good learned dictionary. The zeros in sparse domain give us an idea to reconstruct the pixels that are corrupted by random-value impulse noises. This idea comes from this reality that noisy image in sparse domain of original image will not have a sparse representation as much as original image sparsity. In this method we assume that the proper dictionary to achieve image in sparse domain is available.
KW - Image De-noising
KW - Impulsive noise
KW - Iterative method
KW - Sparsity
UR - http://www.scopus.com/inward/record.url?scp=78650283034&partnerID=8YFLogxK
U2 - 10.1109/ISSPA.2010.5605449
DO - 10.1109/ISSPA.2010.5605449
M3 - Conference contribution
AN - SCOPUS:78650283034
SN - 9781424471676
T3 - 10th International Conference on Information Sciences, Signal Processing and their Applications, ISSPA 2010
SP - 480
EP - 483
BT - 10th International Conference on Information Sciences, Signal Processing and their Applications, ISSPA 2010
T2 - 10th International Conference on Information Sciences, Signal Processing and their Applications, ISSPA 2010
Y2 - 10 May 2010 through 13 May 2010
ER -