International Journal of Computer Applications |
Foundation of Computer Science (FCS), NY, USA |
Volume 141 - Number 1 |
Year of Publication: 2016 |
Authors: R.M. Farouk, Mohammed Elsayed, Mohammed Aly |
10.5120/ijca2016909209 |
R.M. Farouk, Mohammed Elsayed, Mohammed Aly . Medical Image Denoising based on Log-Gabor Wavelet Dictionary and K-SVD Algorithm. International Journal of Computer Applications. 141, 1 ( May 2016), 27-32. DOI=10.5120/ijca2016909209
Medical image denoising is the main step in medical diagnosis, which removes the noise without affecting relevant features of the image. There are many algorithms that can be used to reduce the noise such as: threshold and the sparse representation. The K-SVD is one of the most popular sparse representation algorithms, which is depend on Orthogonal Matching Pursuit (OMP) and Discrete Cosine Transform (DCT) dictionary. In this paper, an algorithm for image denoising was designed to develop K-SVD by using Regularized Orthogonal Matching Pursuit (ROMP) over log Gabor wavelet adaptive dictionary. To evaluate the performance of the proposed techniques, the results were compared with the results of DCT and Gabor wavelet dictionary. The numerical results show that the performance of our algorithm is more efficient in medical image denoising.