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

Abstract：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.

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

1.基于高光譜圖像主成分圖像選取與圖像融合的彩繪文物圖案挖掘

摘要：彩繪文物易碎且珍貴，傳統(tǒng)的分析方法已不適用于彩繪文物。針對這一問題，提出了一個新的領(lǐng)域：高光譜成像技術(shù)可以在可見光至近紅外光范圍內(nèi)對圖像進(jìn)行觀測，且不損傷彩繪文物。本文提出一種自動挖掘彩繪文物圖案的方法。該方法采用最小噪聲分率法獲取主成分圖像，利用顯著性目標(biāo)檢測方法獲取主成分圖像中的顯著圖像，選取平均梯度值最大的顯著性圖像對應(yīng)的主成分圖像作為*優(yōu)主成分圖像，將*優(yōu)主成分圖像與真彩色圖像進(jìn)行融合，得到彩繪文物圖像，從而挖掘出其中的圖案。實(shí)驗數(shù)據(jù)包括陶器和壁畫。結(jié)果表明,所提方法能自動、有效地挖掘人眼不易觀察到的彩繪文物圖案信息。

關(guān)鍵詞:彩繪文物、圖案挖掘、高光譜圖像、最小噪聲分?jǐn)?shù)、顯著目標(biāo)檢測、融合

期刊：Journal of Cultural Heritage

2.Hyperspectral imaging and analysis for sketch painting.

Abstract:Spectral analysis is a practical analytical technique suitable for the study of painting. Especially hyperspectral imaging has gradually become a hot research topic in the scientific analysis of painting relics, due to its characteristics such as non-invasive, non-contact, fast imaging and high spectral resolution. It is mainly used to extract the intrinsic information that is difficult to observe in painting with naked eyes. In this study, two seemingly identical sketch paintings served as samples, one was painted with a 2B pencil, the other with a 4B pencil. A ground-based hyper spectral imager was used to obtain the hyperspectral data cube for the two sketch paintings in the range of 390 nm–1025 nm. And the two paintings were analyzed and compared in terms of spectral characteristics. Results indicated that hyperspectral imaging greatly facilitates the ac quisition of the diagnostic spectral characteristics of different materials in painting. And the specific target in paintings can be effectively identified through hyperspectral analysis, which is of great help to painting identification. At the same time, DC characteristics and detail char acteristics of the painting can be extracted, which are helpful for the researchers to analyze the painting style. In brief, it is further proved that the hyperspectral imaging has significant sci entific and practical value in the protection and preservation of painting relics.

Keywords:Sketch painting Scientific analysis Hyperspectral imaging Spectral characteristic Painting style

2.素描畫的高光譜成像與分析

摘要：光譜分析是一種適用于繪畫研究的實(shí)用分析技術(shù)，尤其是高光譜成像技術(shù)，以其無損、非接觸、快速成像、高光譜分辨率等特點(diǎn)，逐漸成為繪畫文物科學(xué)分析的熱點(diǎn)研究課題，主要用于提取繪畫中肉眼難以觀察到的內(nèi)在信息。本研究以兩幅看似相同的素描畫為樣本，一幅用2B鉛筆繪制，另一幅用4B鉛筆繪制。利用地面高光譜成像儀獲取兩幅素描畫在390nm–1025nm范圍內(nèi)的高光譜數(shù)據(jù)立方體，并對兩幅畫的光譜特征進(jìn)行分析比較。結(jié)果表明，高光譜成像極大地方便了獲取繪畫中不同材質(zhì)的診斷光譜特征，通過高光譜分析可以有效地識別畫作中的特定目標(biāo)，對畫作鑒定有很大幫助。同時，可以提取畫作的直流特征和細(xì)節(jié)特征，有助于研究者分析畫作的風(fēng)格，進(jìn)一步證明了高光譜成像在繪畫文物保護(hù)與保存中具有重要的科學(xué)價值和實(shí)用價值。

關(guān)鍵詞：素描畫、科學(xué)分析、高光譜成像、光譜特征、繪畫風(fēng)格

期刊：Optik-International Journal for Light and Electron Optics