Multi-focus Image Fusion Based on Quadtree Decomposition and Adaptive Focus Measure

Abstract

Abstract: In order to overcome the problem that the block-based fusion method is sensitive to the size of the block and the artifacts in the fused image, a new multi-focus image fusion method based on quadtree decomposition and adaptive focus measurement is proposed. Firstly, according to a new adaptive focus measure based on the sum of modified Laplacian （SML） and guided filtering, it is used to obtain the focus map of the source image. Then, using a new quadtree decomposition strategy and combining the obtained focus map, the source image is further decomposed into tree blocks of optimal size, the focus area is detected from the tree blocks, and a decision map is formed. Finally, the consistency of the decision graph is optimized and verified, and a fully focused image is reconstructed. Through experiments on public multi-focus image data sets, visual quality and objective indicators are compared with 9 advanced fusion methods. The experimental results show that the fusion method proposed in this paper has achieved better performance.

Key words: multi-focus image fusion, focus measure, quadtree decomposition, guided filtering, sum of modified Laplacian.

WANG Ji-wei, QU Huai-jing, WEI Ya-nan, XIE Ming, XU Jia, ZHANG Zhi-sheng, ZHANG Han-yuan. Multi-focus Image Fusion Based on Quadtree Decomposition and Adaptive Focus Measure[J]. Computer and Modernization, 2022, 0(08): 106-113.

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