Abstract

In the inpainting method for object removal, SSD (Sum of Squared Differences) is commonly used to measure the degree of similarity between the exemplar patch and the target patch, which has a very important impact on the restoration results. Although the matching rule is relatively simple, it is likely to lead to the occurrence of mismatch error. Even worse, the error may be accumulated along with the process continues. Finally some unexpected objects may be introduced into the target region, making the result unable to meet the requirements of visual consistency. In view of these problems, we propose an inpainting method for object removal based on difference degree constraint. Firstly, we define the MSD (Mean of Squared Differences) and use it to measure the degree of differences between corresponding pixels at known positions in the target patch and the exemplar patch. Secondly, we define the SMD (Square of Mean Differences) and use it to measure the degree of differences between the pixels at known positions in the target patch and the pixels at unknown positions in the exemplar patch. Thirdly, based on MSD and SMD, we define a new matching rule and use it to find the most similar exemplar patch in the source region. Finally, we use the exemplar patch to restore the target patch. Experimental results show that the proposed method can effectively prevent the occurrence of mismatch error and improve the restoration effect.

Highlights

  • IntroductionIts basic idea is to use the undamaged and effective information to restore the damaged regions according to certain rules [11, 30]

  • Image inpainting derives from the restoration of damaged artworks [5]

  • Some undesired objects will be introduced into the restored region, and the restoration results cannot meet the requirements of human vision. In view of these problems, we propose an image inpainting method for object removal based on difference degree constraint

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Summary

Introduction

Its basic idea is to use the undamaged and effective information to restore the damaged regions according to certain rules [11, 30]. With the rapid development of computer and multimedia technology, the inpainting technology has been widely used in many fields [20], such as Multimedia Tools and Applications (2021) 80:4607–4626 scratches restoration of old photos and precious literatures, protection of cultural relics [8, 18], robot vision, film and television special effects production, and so on [3, 37]. Its basic idea is that the missing region is filled smoothly by diffusing the effective information from the undamaged region into the damaged region at the pixel level [35]. For the small and non-textured damaged regions, these approaches can achieve convincingly excellent result, but for the large and textured missing regions they tend to induce over-smooth effect or stair-case effect

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