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- W2998222133 abstract "Image is an important carrier of information, but the existence of noise will affect the quality and efficiency of information interaction. Image denoising is a classical problem in image processing, in order to improve the denoising effect, we proposed a method based on improved K-SVD algorithm. First, the high frequency and low frequency of the original noisy image are separated. Besides, the improved K-SVD algorithm is used for sparse reconstruction of the high frequency part of the image. Finally, the denoised high frequency part and the low frequency part are superimposed to make the final clean image. The experiments show that this method can achieve better denoising effect compared with DCT based denoising algorithm, K-SVD algorithm and LC-KSVD model." @default.
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- W2998222133 date "2019-01-01" @default.
- W2998222133 modified "2023-09-23" @default.
- W2998222133 title "Image Denoising Based on Sparse Representation over Learned Dictionaries" @default.
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- W2998222133 doi "https://doi.org/10.1007/978-3-030-37352-8_41" @default.
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