Study on Digital Image Inpainting Method Based on Multispectral Image Decomposition Synthesis

Author:

Jia Zhaoyang1ORCID,Chen Guangxue2

Affiliation:

1. College of Packaging & Printing Engineering, Tianjin University of Science & Technology, Tianjin 300222, P. R. China

2. State Key Laboratory of Pulp and Paper Engineering, South China University of Technology, Guangzhou 510640, P. R. China

Abstract

The paper analyzes the image inpainting problem of damaged Painting Arts for high fidelity images reproduction, and a digital image inpainting method based on multispectral image decomposition synthesis is proposed. Firstly, multi-channel images of Painting Arts are obtained by multispectral technology. Then, a polynomial regression method based on principal component is used to reconstruct the spectral image. The reconstructed image is decomposed by VO image decomposition model. During the inpainting process, the channel correlation of the structure image and the texture image of multispectral image is effectively removed. The digital image inpainting is performed respectively. Finally, the digital inpainted image is obtained by synthesis. The experimental results show that the digital image inpainting based on multispectral image decomposition synthesis reduces the problem of low image inpainting accuracy caused by the correlation between the color components in the traditional digital image inpainting process, and reduces the mismatch of the inpainting image. Appearance of pseudo color of inpainting image is reduced. MSE of multispectral images inpainting qualities is 2.7951 and PSNR of multispectral images inpainting qualities is 44.1681, so it is superior to traditional image inpainting algorithm. It provides a reliable basis for digital inpainting, digital archives and high fidelity replication of defective Painting Arts.

Funder

the College Students Innovation and Entrepreneurship Training Program of Tianjin University of Science and Technology.

Publisher

World Scientific Pub Co Pte Lt

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Software

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