Mining painted cultural relic patterns based on principal component images selection and image fusion of hyperspectral images

作者：Peng, Jinye; Yu, Kai; Wang, Jun^*; Zhang, Qunxi; Wang, Lin; Fan, Ping

来源：Journal of Cultural Heritage, 2019, 36: 32-39.

DOI：10.1016/j.culher.2018.09.008

• Painted cultural relic
• Pattern mining
• Hyperspectral image
• Minimum noise fraction
• Salient object detection
• Fusion

Because painted cultural relics are fragile and precious, traditional methods aren't suitable for analyzing them. A new domain is proposed to resolve this question: hyperspectral imaging technology can observe images when the range of the image is from visible to near infrared light. Further, this can be done without damaging the painted cultural relics. This paper presents a method that can automatically mine painted cultural relic patterns. With this method, the principal component images are obtained via the minimum noise fraction method. A salient object detection method is used to obtain the striking images of the principal component images. The principal component image corresponding to the salient image with the largest average gradient value is selected as the optimal principal component image. The optimal principal component image and true color image are fused, in order to obtain a painted culture relic image so that the patterns are mined. Experimental data includes pottery and murals. The results show that the proposed method can automatically and effectively mine painted cultural relic pattern information that is not easily observed by the human eye.

• 出版日期2019-3
• 单位西北大学