Convolutional Sparse Coding-based Image Decomposition
نویسندگان
چکیده
We propose a novel sparsity-based method for cartoon and texture decomposition based on Convolutional Sparse Coding (CSC). Our method first learns a set of generic filters that can sparsely represent cartoon and texture type images. Then using these learned filters, we propose a sparsity-based optimization framework to decompose a given image into cartoon and texture components. By working directly on the whole image, the proposed image separation algorithm does not need to divide the image into overlapping patches for leaning local dictionaries. Extensive experiments show that the proposed method performs favorably compared to state-of-the-art image separation methods.
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