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Sensors 2014, 14(12), 22408-22430; doi:10.3390/s141222408

Dual-Tree Complex Wavelet Transform and Image Block Residual-Based Multi-Focus Image Fusion in Visual Sensor Networks

1
School of Information Technology, Jiangxi University of Finance and Economics, Nanchang 330032, China
2
School of Software and Communication Engineering, Jiangxi University of Finance and Economics, Nanchang 330032, China
3
Key Laboratory of Biomedical Information Engineering of Education Ministry, Institute of Biomedical Engineering, Xi'an Jiaotong University, Xi'an 710049, China
*
Author to whom correspondence should be addressed.
Received: 30 September 2014 / Revised: 11 November 2014 / Accepted: 14 November 2014 / Published: 26 November 2014
(This article belongs to the Special Issue Sensor Computing for Mobile Security and Big Data Analytics)
View Full-Text   |   Download PDF [2837 KB, uploaded 26 November 2014]   |  

Abstract

This paper presents a novel framework for the fusion of multi-focus images explicitly designed for visual sensor network (VSN) environments. Multi-scale based fusion methods can often obtain fused images with good visual effect. However, because of the defects of the fusion rules, it is almost impossible to completely avoid the loss of useful information in the thus obtained fused images. The proposed fusion scheme can be divided into two processes: initial fusion and final fusion. The initial fusion is based on a dual-tree complex wavelet transform (DTCWT). The Sum-Modified-Laplacian (SML)-based visual contrast and SML are employed to fuse the low- and high-frequency coefficients, respectively, and an initial composited image is obtained. In the final fusion process, the image block residuals technique and consistency verification are used to detect the focusing areas and then a decision map is obtained. The map is used to guide how to achieve the final fused image. The performance of the proposed method was extensively tested on a number of multi-focus images, including no-referenced images, referenced images, and images with different noise levels. The experimental results clearly indicate that the proposed method outperformed various state-of-the-art fusion methods, in terms of both subjective and objective evaluations, and is more suitable for VSNs. View Full-Text
Keywords: multi-focus image fusion; dual-tree complex wavelet transform; image block residual; visual sensor networks multi-focus image fusion; dual-tree complex wavelet transform; image block residual; visual sensor networks
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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. (CC BY 4.0).

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Yang, Y.; Tong, S.; Huang, S.; Lin, P. Dual-Tree Complex Wavelet Transform and Image Block Residual-Based Multi-Focus Image Fusion in Visual Sensor Networks. Sensors 2014, 14, 22408-22430.

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