TY - GEN
T1 - Morphology and Active Contour Model for Multi-Focus Image Fusion
AU - Bai, Xiangzhi
AU - Liu, Miaoming
AU - Chen, Zhiguo
AU - Wang, Peng
AU - Zhang, Yu
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2015
Y1 - 2015
N2 - Multi-focus image fusion is an important technique that extracts sharpness regions from multiple images and composites them into a fully focused image. In this paper, a novel spatial domain based fusion algorithm for multi-focus image through gradient based decision map construction using morphology and active contour model is proposed. Firstly, the original focus maps are constructed based on the gradient of the images. Secondly, the coarse focus maps are produced by employing convolution on the original focus maps with a weighted kernel and then the final focus map is decided by the coarse focus maps. Thirdly, the original fusion decision map is obtained by processing the final focus map with morphological opening-And-closing operations and small object removing operation. Fourthly, the extracted boundaries are used as the initial value of the free boundary conditions active contour model and the final decision map is acquired according the original decision map and the boundary map. Finally, the fused image is produced based on the final decision map and the fusion rule. Experimental results show that the proposed algorithm performs better than the other five representative fusion algorithms in both the qualitative and quantitative evaluations.
AB - Multi-focus image fusion is an important technique that extracts sharpness regions from multiple images and composites them into a fully focused image. In this paper, a novel spatial domain based fusion algorithm for multi-focus image through gradient based decision map construction using morphology and active contour model is proposed. Firstly, the original focus maps are constructed based on the gradient of the images. Secondly, the coarse focus maps are produced by employing convolution on the original focus maps with a weighted kernel and then the final focus map is decided by the coarse focus maps. Thirdly, the original fusion decision map is obtained by processing the final focus map with morphological opening-And-closing operations and small object removing operation. Fourthly, the extracted boundaries are used as the initial value of the free boundary conditions active contour model and the final decision map is acquired according the original decision map and the boundary map. Finally, the fused image is produced based on the final decision map and the fusion rule. Experimental results show that the proposed algorithm performs better than the other five representative fusion algorithms in both the qualitative and quantitative evaluations.
UR - https://www.scopus.com/pages/publications/84963648071
U2 - 10.1109/DICTA.2015.7371286
DO - 10.1109/DICTA.2015.7371286
M3 - 会议稿件
AN - SCOPUS:84963648071
T3 - 2015 International Conference on Digital Image Computing: Techniques and Applications, DICTA 2015
BT - 2015 International Conference on Digital Image Computing
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - International Conference on Digital Image Computing: Techniques and Applications, DICTA 2015
Y2 - 23 November 2015 through 25 November 2015
ER -