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Image restoration method based on image segmentation, and system therefor

A repair method and image technology, which is applied in image analysis, image enhancement, image data processing, etc., can solve problems such as failure to find matching texture blocks, lagging repair sequence, unsatisfactory repair results, etc.

Inactive Publication Date: 2010-03-03
BEIJING JIAOTONG UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0008] The example-based image restoration method copies rich texture information to the damaged area, so it can deal with large-area image damage. Compared with other techniques, it can obtain better visual effects, but there are also some shortcomings: (1) The calculation of the priority of boundary pixels is too simple, and the order of repairing the relatively flat low-texture area is obviously lagging behind, which may easily cause excessive expansion of the high-texture area to the low-texture area of ​​the repaired image; (2) When the algorithm is looking for matching blocks, most of them use is a global search method
When this search method contains a lot of noise in the image, the texture synthesis stage often cannot find a suitable matching texture block, which easily leads to matching errors, and as the filling process proceeds, it will also be extended to the subsequent propagation process, resulting in repair The result is not ideal

Method used

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  • Image restoration method based on image segmentation, and system therefor
  • Image restoration method based on image segmentation, and system therefor
  • Image restoration method based on image segmentation, and system therefor

Examples

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Embodiment 1

[0065] The main workflow of the image restoration method of the present invention is as follows: figure 1 As shown, the steps of the image restoration method are:

[0066] (1) Identify the area to be repaired: the user manually selects and identifies the area to be repaired in the image. After the identification is completed, the initial filling front δΩ is obtained 0 ;

[0067] (2) Image region segmentation: use the mean shift algorithm to divide the image into multiple regions, and generate a region segmentation map with the same filling front edge as the initial filling front edge;

[0068] (3) Iteratively filling the area to be repaired: Repeat iterations until all pixels in the area to be repaired are filled, that is, the current filled area The iterative steps are repeated as follows:

[0069] The first step is to calculate the filling priority, that is, to calculate the priority of all target blocks on the current filling edge.

[0070] Suppose the image I is the i...

Embodiment 2

[0095] Such as figure 2 Shown according to a kind of image restoration system based on image region segmentation of the present invention, it comprises the following modules:

[0096] Identify the area to be repaired module, which enables the user to manually select and identify the area to be repaired in the image. After the identification is completed, the initial filling front δΩ is obtained 0 ;

[0097] An image region segmentation module, which uses a mean shift algorithm to divide the identified image to be repaired into multiple regions, and generates a region segmentation map with the same filling front edge as the initial filling front edge; and,

[0098] Repeat the iteration module, which iterates repeatedly in the area to be repaired until all pixels in the area to be repaired are filled, that is, the current filled area

[0099] In this embodiment, the repeated iteration module includes:

[0100] Calculating the filling priority module, which is responsible f...

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Abstract

The invention discloses an image restoration method based on image segmentation, and a system therefor; the method comprises: firstly, manually selecting and marking the area to be restored in image by a user; then, carrying out image domain decomposition by mean shift algorithm, and dividing the image into a number of areas; finally, carrying out repeated iterative operation on the area to be restored until all pixels in the area to be restored is filled to be full. The method optimizes the calculation of priority in image restoration algorithm, thus effectively preventing the over expansionof the restored image from a high-texture area to a low-texture area; furthermore, matched block searching standard based on the image domain decomposition can be formulated on that basis, so that anerroneous block can be avoided being introduced; compared with the original image restoration method based on the sample, the effect of the method is more in accordance with the visual expectation ofhuman beings; furthermore, at present, the method is successfully applied to large size area restoration of various images with complex texture and structural characteristics as well as the aspects such as wiping off characters, removing target objects and the like.

Description

technical field [0001] The invention relates to an image restoration method for a large-scale area, belonging to the fields of digital image processing and computer vision. Background technique [0002] Digital image repair technology belongs to the research field of image restoration. Its purpose is to study and solve how to better detect the damaged part of the image, and then use the image repair algorithm to repair the damaged part of the image according to the effective information around the damaged part of the image. Automatic recovery. In recent years, digital image restoration technology has a wide range of applications in pre-press image processing, cultural relic image restoration, film and television special effects production, virtual reality, biomedicine, obstacle removal (such as: deleting some objects, text, titles, etc. in video images) and so on. Application prospects. [0003] According to the size and shape of the area to be inpainted, image inpainting ...

Claims

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Application Information

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IPC IPC(8): G06T5/00G06T7/00
CPCG06T7/11G06T5/77
Inventor 苗振江张如唐振
Owner BEIJING JIAOTONG UNIV
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