Multi-focus image fusion with half weighted gradient and self-similarity

Abstract

In order to get a satisfactory image fusion effect, getting a focus map is very necessary and usually difficult to finish. In this paper, we address this problem with a half weighted gradient approach, aiming to obtain a direct mapping between focus map and source images. Based on the advantages of multi-scale weighted gradient, while abandoning the shortcomings of weighted gradient, a new multi-focus image fusion method called half weighted gradient and self-similarity (HWGSS) is proposed. Experimental results validate that the proposed algorithm can obtain state-of-the-art fusion performance in terms of both qualitative and quantitative evaluations.

Keywords

A

References

[1] Burt P., Adelson E.. IEEE Trans. Commun.. 1983, 31: 532

[2] Toet A.. Pattern Recognit. Lett.. 1989, 9: 255

[3] Li H., Manjunath B., Mitra S.. Graphical Models Image Process.. 1995, 57: 235

[4] Lewis J., Oí Callaghan R., Nikolov S., Bull D., Canagarajah N.. Inf. Fusion. 2007, 8: 119

[5] Zhang Q., Guo B.. Signal Process.. 2009, 89: 1334

[6] Huang W., Jing Z.. Pattern Recognit. Lett.. 2007, 28: 493

[7] Li S., Kwok J., Wang Y.. Inf. Fusion. 2001, 2: 169

[8] Aslantas V., Kurban R.. Expert Syst. Appl.. 2010, 37: 8861

[9] Bai X., Zhang Y., Zhou F., Xue B.. Inf. Fusion. 2015, 22: 105

[10] Du C., Gao S.. IEEE Access. 2017, 5: 15750

[11] Li S., Kang X., Hu J.. IEEE Trans. Image Process.. 2013, 22: 2864

[12] Liu Y., Liu S., Wang Z.. Inf. Fusion. 2015, 23: 139

[13] Zhou Z., Li S., Wang B.. Inf. Fusion. 2014, 20: 60

[14] Guo D., Yan J.W., Qu X.. Optics Communications. 2015, 338: 138

[15] Liu Y., Chen X., Peng H., Wang Z.. Inf. Fusion. 2017, 36: 191

[16] Yong Y., Song T., Shuying H., Pan L.. IEEE Sensors Journal. 2015, 15: 2824