Research On Image Segmentation For Virtual Color Restoration Of Ancient Murals

China has a large number of coloured cultural relics and works of art,which carry the splendid civilisation and history and culture of our country and have significant historical value,while the colour information is an essential carrier for the expression and transmission of the historical and cultural attributes of the relics themselves.Due to the influence of external factors,cultural relics have suffered serious disease problems,resulting in the change or loss of information about their apparent value.In this paper,we propose a super-pixel-based image segmentation method and a spectral replacement-based colour high-fidelity digital virtual restoration method to address the problems of image segmentation and high-fidelity colour restoration of ancient wall paintings in computer-aided digital restoration technology and achieve more satisfactory results.1)To address the problem of achieving fine-grained segmentation of ancient mural images.Ancient frescoes are characterised by a rich variety of colours and the fusion of different colours with each other,coupled with fading,peeling,wear and tear and other serious damage to the colours of the frescoes,making the traditional segmentation algorithm at the pixel level a single use to segment the target image will result in over-segmentation,while at the superpixel level will result in under-segmentation problems,to achieve the goal of refinement of segmentation basically take the traditional segmentation methods and humancomputer interaction In order to achieve finer segmentation of the target,traditional segmentation methods and human-computer interaction are basically adopted.Deep learningbased image segmentation methods require a large number of training samples,and it is difficult to produce training samples for ancient wall painting images.To address the above existing problems,a super-pixel-based optimised segmentation method for ancient mural images is proposed to achieve the goal of refined segmentation of ancient mural images.2)For high-fidelity digital restoration of colour.Traditional colour restoration techniques for ancient fresco images are limited by the inherent "homochromatic" problem of chromaticity,therefore,colour restoration techniques based on chromaticity are conditional on colour processing and have significant limitations in applications such as high-fidelity colour digital capture and reproduction.In order to address the problem of high-fidelity colour restoration of ancient wall painting images,we use spectral reflectance replacement to achieve high-fidelity colour acquisition and reproduction and realise the faded colour simulation of ancient wall painting images based on a spectral-based faded colour model,realising high-fidelity colour digital restoration of ancient wall painting images.The validity and superiority of the methods are examined using Dunhuang simulated murals and actual murals.Based on the proposed segmentation algorithm and the spectral reflectance fading model,i.e.the spectral fading model,the fading process of lead-containing pigments in simulated murals is simulated,and a high-fidelity virtual evolution of the colour of ancient mural images based on spectral replacement is achieved.The experimental results show that the algorithm proposed in this paper is able to obtain refined segmentation results with clear boundaries,and the colour high-fidelity digital simulation experiments are carried out based on the optimised segmentation method,which provides overall methodological support for the colour high-fidelity digital restoration of faded ancient wall painting images.