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Bayes non-local mean image restoration method

A local mean image and repair method technology, applied in the field of image repair, can solve the problems that the repair result cannot connect the detailed texture well, and the calculation of the similarity weight is not accurate enough, etc.

Inactive Publication Date: 2012-11-28
XIDIAN UNIV
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Problems solved by technology

However, this method uses a negative exponential function with a constant attenuation coefficient to calculate the similarity weight between the sample block and the block to be repaired, and the information contained in different blocks to be repaired is different, which will inevitably lead to similarity The calculation of the weight is not accurate enough, which leads to the inpainting result not being able to connect the detailed texture in the image well

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  • Bayes non-local mean image restoration method
  • Bayes non-local mean image restoration method
  • Bayes non-local mean image restoration method

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Embodiment Construction

[0039] refer to figure 1 , the implementation steps of the present invention are as follows:

[0040] Step 1, read in the image I to be repaired, for example figure 2 , Figure 4 or Figure 6 , determine the area to be repaired Ω and its boundary δ.

[0041] Step 2, calculate the priority of all blocks whose center point is on the boundary δ:

[0042] (2.1) Define D(p) as a data item, C(p) as a confidence item, which represents the credibility of the image pixel, and initialize C(p): C(p)=0, p∈Ω, C(p)=1, p∈I-Ω;

[0043] (2.2) Use the following formula to calculate the confidence item C(p) and data item D(p):

[0044] C ( p ) = Σ q ∈ ψ pI ( I - ...

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Abstract

The invention discloses a Bayes non-local image restoration method which mainly solves the problems that the search of similar blocks is inaccurate and a parameter value is determined by experience in the existing sample-based non-local mean image restoration method. The method comprises the following steps: (1) determining a to-be-restored area omega and the boundary delta thereof for a to-be-restored image I; (2) finding a restoration block with the highest priority on the boundary, and modeling by use of a Bayesian framework; (3) pre-selecting a search area by use of an adaptive threshold; (4) searching for m sample blocks the most similar to the restoration block, and taking the weighted mean of the m sample blocks as a filling block of the restoration block; and (5) updating the confidence item and the to-be-restored area, and repeating the steps (1) to (5) until all points in the to-be-restored area are restored. The method disclosed by the invention can be used for restoring the image-damaged area, restoring the image scratch and removing the text in the image.

Description

technical field [0001] The invention belongs to the technical field of image processing, relates to image restoration, and can be used for repairing damaged areas in images, image scratches and text removal in images. Background technique [0002] Image information has become an important source of information for human beings and an important means of using information due to its advantages of large amount of information, fast transmission speed, and long distance. However, images in reality will lose image information due to various reasons. Image restoration techniques are used. [0003] The purpose of image restoration is to automatically restore lost information based on the existing information of the image, which can be used to restore lost information in old photos, remove video text, and hide video errors. Existing image inpainting methods can be roughly divided into two categories: structure-based inpainting methods and texture-based inpainting methods. Among the...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T5/50
Inventor 钟桦焦李成朱波王桂婷侯彪王爽张小华田小林
Owner XIDIAN UNIV