JOURNAL ARTICLE

Multi-focus image fusion using a guided-filter-based difference image

Xiang YanHanlin QinJia LiHuixin ZhouTingwu Yang

Year: 2016 Journal:   Applied Optics Vol: 55 (9)Pages: 2230-2230   Publisher: Optica Publishing Group

Abstract

The aim of multi-focus image fusion technology is to integrate different partially focused images into one all-focused image. To realize this goal, a new multi-focus image fusion method based on a guided filter is proposed and an efficient salient feature extraction method is presented in this paper. Furthermore, feature extraction is primarily the main objective of the present work. Based on salient feature extraction, the guided filter is first used to acquire the smoothing image containing the most sharpness regions. To obtain the initial fusion map, we compose a mixed focus measure by combining the variance of image intensities and the energy of the image gradient together. Then, the initial fusion map is further processed by a morphological filter to obtain a good reprocessed fusion map. Lastly, the final fusion map is determined via the reprocessed fusion map and is optimized by a guided filter. Experimental results demonstrate that the proposed method does markedly improve the fusion performance compared to previous fusion methods and can be competitive with or even outperform state-of-the-art fusion methods in terms of both subjective visual effects and objective quality metrics.

Keywords:
Image fusion Artificial intelligence Filter (signal processing) Computer science Fusion Computer vision Focus (optics) Feature extraction Feature (linguistics) Composite image filter Smoothing Pattern recognition (psychology) Image (mathematics) Optics Physics

Metrics

38
Cited By
4.68
FWCI (Field Weighted Citation Impact)
33
Refs
0.96
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Advanced Image Fusion Techniques
Physical Sciences →  Engineering →  Media Technology
Remote-Sensing Image Classification
Physical Sciences →  Engineering →  Media Technology
Image Enhancement Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition

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