Multi-Focus Image Fusion Using Sparse Representation And Modified Difference

PATTERN RECOGNITION AND MACHINE INTELLIGENCE, PREMI 2019, PT I(2019)

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摘要
Multi-focus fusion technique is used to combine images obtained from single or different cameras with different focal distance, etc. In the proposed method, the non-subsampled shearlet transform (NSST) is employed to decompose the input image data into the low-frequency and high-frequency bands. These low-frequency and highfrequency bands are combined using sparse representation (SR) and modified difference based fusion rules, respectively. Then, inverse NSST is employed to get the fused image. Both qualitative and quantitative results confirm that the proposed approach yields a better performance as compared to state-of-the-art fusion schemes.
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关键词
Image fusion, K-SVD, Cosine bases, Multi-focus, Sparse representation, Dictionary learning
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