Image fusion based on object region detection and Non-Subsampled Contourlet Transform. (August 2017)

• Record Type: Journal Article
• Authors: Meng, Fanjie; Song, Miao; Guo, Baolong; Shi, Ruixia; Shan, Dalong
• Is Part Of: Computers & electrical engineering. Volume 62(2017)
• Page Start: 375
• Page End: 383
• Publication Date: 2017-08
• Subjects: Image fusion -- Object region detection -- The Non-Subsampled Contourlet Transform -- Fusion rule; Computer engineering -- Periodicals; Electrical engineering -- Periodicals; Electrical engineering -- Data processing -- Periodicals; Ordinateurs -- Conception et construction -- Périodiques; Électrotechnique -- Périodiques; Électrotechnique -- Informatique -- Périodiques; Computer engineering; Electrical engineering; Electrical engineering -- Data processing; Periodicals; Electronic journals; 621.302854
• DOI: 10.1016/j.compeleceng.2016.09.019
• Languages: English
• ISSNs: 0045-7906

Abstract

Abstract: This paper presents a new fusion algorithm for infrared (IR) and visible light (ViS) images by combining object region detection with the Non-Subsampled Contourlet Transform (NSCT). First, the saliency map for the IR image is acquired with saliency detection. Second, the object region in the IR image is extracted by introducing a free regions removal method. Third, source images are decomposed via NSCT and different fusion rules for low frequency sub-bands and high frequency sub-bands are employed. Then, the primary fused image is generated by the inverse NSCT. Finally, integrating the primary fused image with the object region, the final fused image is obtained. By conducting experiments, we compare our method to others using several metrics and results show that the proposed method can improve the quality of the fused image.