Title :
Image denoising with gradient projection
Author :
Chen, Yiping ; Li, Xiang
Author_Institution :
Coll. of Electron. Sci. & Eng., Nat. Univ. of Defense Technol., Changsha, China
Abstract :
Image denoising can be modeled as a minimization problem of L2 norm. This problem mostly is solved using L2-norm methods previously. However, L2-norm methods may smooth the results. In this paper, this problem is solved efficiently by gradient projection, in particular, minimization with L1-norm penalty as we proposed. A variable splitting technique is employed to make the L1 norm penalty function differentiable. We present a L1-norm gradient projection approach to image denoising problem where the denoising is subject to minimization with nonnegative constraints. Numerical experiments and comparisons demonstrate the effectiveness of the proposed approach.
Keywords :
gradient methods; image denoising; L1-norm penalty; gradient projection; image denoising; nonnegative constraints; variable splitting technique; Equations; Image denoising; Mathematical model; Noise measurement; Noise reduction; PSNR; L1 norm; gradient projection; image denoising; regularization;
Conference_Titel :
Signal Processing, Communications and Computing (ICSPCC), 2011 IEEE International Conference on
Conference_Location :
Xi´an
Print_ISBN :
978-1-4577-0893-0
DOI :
10.1109/ICSPCC.2011.6061780