Multi-focus Image Fusion Using Sparse Representation and Modified Difference

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Abstract

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 high-frequency 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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Vishwakarma, A., Bhuyan, M. K., Sarma, D., & Bora, K. (2019). Multi-focus Image Fusion Using Sparse Representation and Modified Difference. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11941 LNCS, pp. 482–489). Springer. https://doi.org/10.1007/978-3-030-34869-4_52

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