Environmental changes and human activities can cause serious degradation of murals, where sootiness is one of the most common problems of ancient Chinese indoor murals. In order to improve the visual quality of the murals, a restoration method is proposed for sootiness murals based on dark channel prior and Retinex by bilateral filter using hyperspectral imaging technology. First, radiometric correction and denoising through band clipping and minimum noise fraction rotation forward and inverse transform were applied to the hyperspectral data of the sootiness mural to produce its denoised reflectance image. Second, a near-infrared band was selected from the reflectance image and combined with the green and blue visible bands to produce a pseudo color image for the subsequent sootiness removal processing. The near-infrared band is selected because it is better penetrating the sootiness layer to a certain extent comparing to other bands. Third, the sootiness covered on the pseudo color image was preliminarily removed by using the method of dark channel prior and by adjusting the brightness of the image. Finally, the Retinex by bilateral filter was performed on the image to get the final restored image, where the sootiness was removed. The results show that the images restored by the proposed method are superior in variance, average gradient, information entropy and gray scale contrast comparing to the results from the traditional methods of homomorphic filtering and Gaussian stretching. The results also show the highest score in comprehensive evaluation of edges, hue and structure; thus, the method proposed can support more potential studies or sootiness removal in real mural paintings with more detailed information. The method proposed shows strong evidence that it can effectively reduce the influence of sootiness on the moral images with more details that can reveal the original appearance of the mural and improve its visual quality.

Environmental changes and human activities can cause serious degradation of murals, where sootiness is one of the most common problems of ancient Chinese indoor murals. In order to improve the visual quality of the murals, a restoration method is proposed for sootiness murals based on dark channel prior and Retinex by bilateral filter using hyperspectral imaging technology. First, radiometric correction and denoising through band clipping and minimum noise fraction rotation forward and inverse transform were applied to the hyperspectral data of the sootiness mural to produce its denoised reflectance image. Second, a near-infrared band was selected from the reflectance image and combined with the green and blue visible bands to synthesize a pseudo color image for the subsequent sootiness removal processing. The near-infrared band is selected because it is better penetrating the sootiness layer to a certain extent comparing to other bands. Third, the sootiness covered on the pseudo color image was preliminarily removed by using the method of dark channel prior and by adjusting the brightness of the image. Finally, the Retinex by bilateral filter was performed on the image to get the final restored image, where the sootiness was removed. The results show that the proposed method can effectively reduce the influence of sootiness on the mural image and improve its visual quality. It can also be used to reveal the original appearance of the mural to reasonable extent.

Background: Hyperspectral technology has made it possible to perform completely non-invasive investigations on pigment analysis, in particular, on pigment identification. The most commonly used method of pigment identification is to compare the spectral similarity between ones of unknown target and ones in spectral library, which requires a comprehensive and complete spectral library and is based on overall shape of the spectrum. To a certain extent, it may ignore some of the key absorption characteristics of the spectrum. Methods: A novel spectral matching method was proposed based on the spectrum divided into subsections for identification according to the main ion absorption characteristics. Main works: (1) establishing a spectral library suitable for typical pigment identification of painting; (2) discussing the main components, as well as the absorption positions of the ions and functional groups contained in pigments frequently used by artists; (3) presenting a novel spectral matching algorithm carried on spectral subsections for pigment identification; (4) verifying the feasibility and applicability of proposed method by a Chinese painting and a fresco. Conclusions: The proposed method can correctly identify the main pigments or components contained in the mixed area, which is better than the traditional method and more convenient than the unmixing method, except for some limitations in detecting white and black pigments.

Hyperspectral imaging technology is a research hotspot in the field of cultural heritage protection. It can be used to quickly and noninvasively obtain detailed spectral information from the surfaces of cultural relics of different categories. We can intuitively analyse pigment compositions, line characteristics, painting skills and patterns using spectral information. Hyperspectral imaging has high scientific significance and application value for the protection, restoration and research of ancient murals and other cultural relics. In this study, a mural from Daheitian hall in the Qutan temple, Qinghai Province, China, was used as a sample. The hyperspectral data were acquired and analysed for several purposes. Pigment spectral matching and abundance inversion were carried out to obtain the pigment distribution. These data were enhanced by continuum removal and histogram stretching to obtain hidden information. The dark channel prior, Criminisi and Retinex methods were used to virtually restore the image of the mural. The results indicated that by using hyperspectral imaging data, the constructed pure pigment spectrum library and suitable approaches, the types and distributions of mural pigments can be quantitatively analysed, and the lines in murals can be extracted. Hyperspectral images are helpful for identifying information hidden by pigments or surface materials. Mural images can be enhanced, and hidden information can be highlighted using enhancement methods, such as continuum removal and histogram linear stretching. In addition, hyperspectral imaging data have unique advantages in the restoration of mural images, and the combination of defogging methods and image inpainting algorithms can realize the virtual restoration of mural images. In brief, hyperspectral imaging technology was found to have a highly favourable effect on pigment analysis, line extraction, information enhancement, hidden information extraction and the virtual restoration of ancient murals.