A novel multi-focus image fusion method based on distributed compressed sensing |
| |
| Affiliation: | 1. Key Laboratory of Electronic Equipment Structure Design, Ministry of Education, Xidian University, Xi''an, Shaanxi 710071,China;2. Center for Complex Systems, School of Mechano-electronic Engineering, Xidian University, Xi''an Shaanxi 710071, China;3. WMG Data Science, University of Warwick, Coventry CV4 AL7, U.K;1. Key Laboratory of Electronic Equipment Structure Design, Ministry of Education, Xidian University, Xi''an, Shaanxi710071, China;2. Center for Complex Systems, School of Mechano-electronic Engineering, Xidian University, Xi''an, Shaanxi710071, China;3. School of Electronic Engineering, Xidian University, Xi''an, Shaanxi710071, China;4. Computer Science Department, Aberystwyth University, Aberystwyth SY23 3FL, United Kingdom |
| |
| Abstract: | Multi-focus image fusion aims to produce an all-in-focus image by merging multiple partially focused images of the same scene. The main work is identifying the focused region and then composing all the focused regions. In this paper, a novel efficient multi-focus image fusion method based on distributed compressed sensing (DCS) is proposed. Firstly, the low-frequency and high-frequency images are obtained by comparing the variance of the source images, which are further utilized to get the low-frequency and high-frequency dictionaries. Secondly, DCS using joint sparsity model-1 (JSM-1) is applied to reconstruct the precise high-frequency images. Thirdly, the decision map is obtained based on all the high-frequency images and then improved by the morphological processing. Finally, the focused pixels are chosen from the source images through the decision map. Experimental results indicate that the proposed DCS-based method can be competitive with or even outperform some state-of-the-art methods in terms of both visual and quantitative metric evaluations. |
| |
| Keywords: | Distributed compressed sensing Decision map Multi-focus image fusion Joint-sparsity-model-1 |
| 本文献已被 ScienceDirect 等数据库收录！ |
|
