Version 1
: Received: 10 November 2016 / Approved: 10 November 2016 / Online: 10 November 2016 (07:34:22 CET)
How to cite:
Lai, M.; Sun, J.; Zhang, L.; Shen, Y.; Yang, Q.; Jin, Z. A Multi-Focus Image Fusion Algorithm Based on Contrast Pyramids. Preprints2016, 2016110057. https://doi.org/10.20944/preprints201611.0057.v1
Lai, M.; Sun, J.; Zhang, L.; Shen, Y.; Yang, Q.; Jin, Z. A Multi-Focus Image Fusion Algorithm Based on Contrast Pyramids. Preprints 2016, 2016110057. https://doi.org/10.20944/preprints201611.0057.v1
Lai, M.; Sun, J.; Zhang, L.; Shen, Y.; Yang, Q.; Jin, Z. A Multi-Focus Image Fusion Algorithm Based on Contrast Pyramids. Preprints2016, 2016110057. https://doi.org/10.20944/preprints201611.0057.v1
APA Style
Lai, M., Sun, J., Zhang, L., Shen, Y., Yang, Q., & Jin, Z. (2016). A Multi-Focus Image Fusion Algorithm Based on Contrast Pyramids. Preprints. https://doi.org/10.20944/preprints201611.0057.v1
Chicago/Turabian Style
Lai, M., Qing Yang and Zilong Jin. 2016 "A Multi-Focus Image Fusion Algorithm Based on Contrast Pyramids" Preprints. https://doi.org/10.20944/preprints201611.0057.v1
Abstract
This paper proposes a new approach for multi-focus images fusion based on Region Mosaicing on Contrast Pyramids (REMCP). A density-based region growing method is developed to construct a focused region mask for multi-focus images. The segmented focused region mask is decomposed into a mask pyramid, which is then used for supervised region mosaicking on a contrast pyramid. In this way, the focus measurement and the continuity of focused regions are incorporated and the pixel level pyramid fusion is improved at the region level. Objective and subjective experiments show that the proposed REMCP is more robust to noise than compared algorithms and can fully preserves the focus information of the multi-focus images meanwhile reducing distortions of the fused images.
Keywords
multi-focus image, image fusion, region mosaic, contrast pyramid
Subject
Engineering, Electrical and Electronic Engineering
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
