Research on Key Technologies of inpainting in 3D Immersive System
In this paper,the key technologies of inpainting of 3D immersive system are deeply studied,and a color image guided CNN structure is proposed to build a depth image compression artifact suppression model based on CNN,which improves the overall quality and edge information of the original intangible cultural relics image,and enhances the restoration effect.Firstly,the basic structure of CNN convolutional neural networks was studied;Then,a CNN based deep image compression artifact suppression model was constructed,and the concept of spectral decomposition was introduced to reconstruct the high-frequency part of the deep image,filtering out useless interference information and accelerating the training convergence speed of the model;And a content repair meth-od based on multi-scale guidance information was designed to enhance the repair effect of the model;Finally,experiments and tests were conducted on the CNN based deep image compression artifact suppression model.The experimental results show that the model constructed with a CNN structure guided by color images,which incorporates grayscale information assistance,performs better in im-age restoration compared to models without grayscale information assistance;The model designed in this article has a peak signal-to-noise ratio of 45.18 when the image quality Q=30,which is 4.31 more than the Liu model with the best neutral energy in the other five experimental control group models;However,when the image quality Q=40,the peak signal to noise ratio is as high as 49.36,an increase of 7.47 over Liu's model,indicating that the inpainting model designed in this paper has better performance,and the in-painting effect has been significantly improved,which can be used for inpainting of intangible cultural relics.
3D immersive systeminpaintingintangible cultural heritage ceramic relicsCNN