Infrared and visible image fusion for ship targets based on scale‐aware feature decomposition. Issue 14 (19th August 2022)

• Record Type: Journal Article
• Authors: Zheng, Xin; Kang, Di; Si, Pengbo; Wu, Qiang
• Is Part Of: IET image processing. Volume 16:Issue 14(2022)
• Page Start: 3977
• Page End: 3987
• Publication Date: 2022-08-19
• Subjects: Image processing -- Periodicals; 621.36705
• DOI: 10.1049/ipr2.12607
• Languages: English
• ISSNs: 1751-9659

Abstract

Abstract: Infrared (IR) and visible (VI) image fusion play an important role in improving the sea scene perception and ship target detection. Although there have been many studies on image fusion considering the sea scene characteristics, there has still been no adequate extraction method for detailed information of a ship target in a sea scene. To overcome this shortcoming, this paper proposes a fusion method based on a scale‐aware feature decomposition, which can accurately extract features of a ship target at different scales. First, a hybrid feature decomposition method based on the scale‐aware structure‐preserving filter and Gaussian filter is designed. The proposed method separated source images into region, structure, and texture layers, and thus achieved a finer‐scale division than traditional multiscale decomposition methods in the sea‐clutter background. Then, further decomposition of the texture layer was performed by the shearlet transform to obtain the directional texture feature. According to the characteristics of each layer, different strategies were adopted for the fusion, and the weighting factor was used to obtain the final fusion result. Experimental results indicated that the proposed method could achieve better subjective and objective results than current state‐of‐the‐art methods. This method introduces a scale‐aware edge preserving filter to improve the ability of detail extraction and is suitable for image fusion of ship targets.