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

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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...

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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...

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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...

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Wavelet Based Self Learning Adaptive Dictionary Algorithm for Image Denoising

Article history: Received on Feb 27th 2015 Accepted on March 20th 2015 Available online 15th June 2015

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ژورنال

عنوان ژورنال: International Journal of Computer Applications

سال: 2012

ISSN: 0975-8887

DOI: 10.5120/9521-3926