In recent years, other diffusion-based methods have been studied for restoring images.
INPAINT REVIEW TV
Therefore, compared with TV model, the CCD model can repair not only images with large damaged areas but also fine edges, especially for gray-scale images. It suppressed the large curvature and protected the small in the restoring process so that the “connectivity criterion” was satisfied. When there was a large curvature anywhere, the isophotes became strong and then gradually weakened as the isophotes extended. Furthermore, Chan and Shen proposed curvature-driven diffusions (CCD) model in which the diffusion process took structure information of contour (curvature term) into account. But, the method merely depended on its gradient values rather than geometric information of the isophotes, which led to the applicability of small missing regions. Motivated by the idea, Chan and Shen proposed the total variation (TV) model which can restore and maintain edge information, while performing denoising by using anisotropic diffusion. proposed the Bertalmio–Sa-piro–Caselles–Ballester-based inpainting method, in which the information around the defective area was propagated from the outside to the inside along the direction of the isophotes in incomplete regions, thereby obtaining the restored image from the damaged one. The first category is diffusion-based methods, where parametric models are established by partial differential equations in order to propagate the local structures from known regions to unknown regions. 1.Ĭurrently, image inpainting methods have been mainly divided into two categories. In the next paragraphs, we introduce several main completion methods and the classification diagram is shown in Fig. Based on this assumption, many researchers have put forward their researches and obtained significant success.
That is, the colors, textures, and geometric structures of the inpainted regions should be similar to those of the ambient regions. In addition, the inpainted image should satisfy the human visual consistency requirement as much as possible. All image completion algorithms are based on a hypothesis that the completed region and the missing region have the same statistical property and geometric structure. The technology is originally developed to renovate damaged photos and films or to remove unwanted texts and the occlusion from images in a plausible way, etc. With the advancement of society and the rapid development of the Internet, image completion, also called image inpainting, has been applied to many fields proverbially, such as the protection of ancient relics, image editing, medical field, and military field.
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