Image Inpainting Algorithm Based on Spherical Convergence and Structure Consistency

To obtain the robust filling order and suitable matching criterion, an image inpainting algorithm based on spherical convergence and structure consistency was proposed. In terms of filling order, on the one hand, the spherical convergence rule was introduced into the definition of the priority criterion to ensure the reasonable extension of the texture and smooth part while maintaining the priority filling of the structural part. On the other hand, a confidence item update criterion based on Stirling theory was constructed to avoid rapid decay of confidence value. In terms of matching criterion, the structural consistency was applied to find a more suitable exemplar for filling to reduce false matching and error accumulation. The experimental results show that compared with the existing image inpainting algorithms, the proposed method can produce a more stable inpainting order, maintain structure coherence and texture consistency of the completed image, effectively reduce error accumulation effect, and obtain a better restoration effect. © 2021, Department of Journal of the China Railway Society. All right reserved.