Benyuan Li

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This paper presents a new approach to single-image super-resolution reconstruction, based on patch haar wavelet feature extraction combined with sparse coding. The training sample set is constructed by image patches haar wavelet transform to extract the horizontal, vertical and diagonal high frequency component composition column feature vector. Then, we(More)
This paper presents a new approach to single-image super-resolution reconstruction, based on sparse signal representation using classified dictionaries. The high-resolution and low-resolution image patches training sets are divided into two categories respectively by two new classification templates which give consideration to direction and edge features.(More)
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