Rapid image repairing method based on sample

Abstract

The invention discloses a rapid image repairing method based on a sample. The rapid image repairing method includes the steps that a to-be-repaired area is determined through marks; a contour line of a boundary of the to-be-repaired area and a known area is selected; a data value and a confidence coefficient value of a template are calculated; adjusting parameters are introduced to determine a to-be-repaired module with the highest priority; in the known area adjacent to the to-be-repaired module, conducting searching from the near to the distant to obtain an optimal matching block according to the distance between the optimal matching block and a center point of the to-be-repaired module; filling the corresponding position of the to-be-repaired module with a pixel point corresponding to the optimal matching block, and meanwhile updating the confidence value of the newly-updated pixel point; repeatedly executing the steps on the to-be-repaired area until the to-be-repaired area is filled completely. The rapid image repairing method is optimized from priority operation, data valve calculation, matching area and optimal matching block searching and confidence value updating, and the repairing effect is more natural; meanwhile, matching only needs to be carried out on a local part during repairing, so that the repairing time is greatly shortened.

Description

technical field [0001] The invention relates to an image restoration method, in particular to a sample-based rapid image restoration method, and belongs to the technical field of image processing. Background technique [0002] As an important application of image processing, the main purpose of image restoration is to restore damaged images to a degree acceptable to the human eye. Its application fields include art restoration, computer animation, film and television special effects, virtual reality, etc. . [0003] The current image repair algorithms mainly focus on two categories: one is the method of image retouching (inpainting), which was first introduced into digital images by Bertalmio et al., using a repair model based on partial differential equations (PDE). There are also the total variational (TV) model proposed by Chan and the curvature-driven diffusion (CDD) model. These methods have a good repair effect on damaged images with flaws, but the effect of repairin...

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Problems solved by technology

[0006] Aiming at the problems existing in the above-mentioned prior art, the present invention provides a sample-based fast image restoration method, which can effectively solve the problem of Criminisi algorithm low-texture region repair lag, and can also ensure that the boundary lines of texture regions of different colors will follow the filling process. It is preserved and continued, and the linear structure of the image is preserved, which is conducive to the elimination of "faults", so that the sequence of restoration and synthesis is basically synthesized from the periphery to the middle, and the final restoration effect is more realistic and natural; Reduce repair time

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