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Multi-focus image fusion using fractal dimension

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Abstract

Multi-focus image fusion is defined as “the combination of a group of partially focused images of a same scene with the objective of producing a fully focused image.” Normally, transform-domain-based image fusion methods preserve the textures and edges in the blend image, but many are translation variant. The translation-invariant transforms produce the same size approximation and detail images, which are more convenient to devise the fusion rules. In this work, a translation-invariant multi-focus image fusion approach using the à-trous wavelet transform is introduced, which uses fractal dimension as a clarity measure for the approximation coefficients and Otsu’s threshold to fuse the detail coefficients. The subjective assessment of the proposed method is carried out using the fusion results of nine state-of-the-art methods. On the other hand, eight fusion quality metrics are considered for the objective assessment. The results of subjective and objective assessment on grayscale and color multi-focus image pairs illustrate that the proposed method is competitive and even better than some of the existing methods.

© 2020 Optical Society of America

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Corrections

Chinmaya Panigrahy, Ayan Seal, Nihar Kumar Mahato, Ondrej Krejcar, and Enrique Herrera-Viedma, "Multi-focus image fusion using fractal dimension: publisher’s note," Appl. Opt. 59, 6593-6593 (2020)
https://opg.optica.org/ao/abstract.cfm?uri=ao-59-22-6593

25 June 2020: A typographical correction was made to the Funding section.


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