Cloud K-SVD for Image Denoising

Quaternion K-SVD for Color Image Denoising

Denoising using the K-SVD Method

Sparse representation of images has been a recent area of growing interest. It finds applications in many problems in image processing. In this report we study a particular method of achieving sparse representation using the recently proposed K-SVD algorithm by Aharon et al. [1] and how this sparse representation framework has been extended to perform denoising, as illustrated by the authors in...

Image Denoising using K-SVD Algorithm based on Gabor Wavelet Dictionary

Image denoising problem can be addressed as an inverse problem. One of the most recent approaches to solve an inverse problem is a sparse decomposition over overcomplete dictionaries. In sparse representation, images are represented as a linear combination of dictionary atoms. In this paper, we propose an algorithm for image denoising based on Orthogonal Matching Pursuit (OMP) for determining s...

Medical Image Denoising based on Log-Gabor Wavelet Dictionary and K-SVD Algorithm

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 Tra...

Medical Image Denoising based on Log-Gabor Wavelet Dictionary and K-SVD Algorithm

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 Tra...