Image restoration method based on curvature driven diffusion

A repair method and image technology, applied in image enhancement, image data processing, instruments, etc., can solve problems such as step effect, long iteration time, slow convergence speed, etc., to avoid false edges and step effect, speed up iteration, avoid The effect of blurred edges

Inactive Publication Date: 2013-07-10
LIAONING NORMAL UNIVERSITY
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  • Abstract
  • Description
  • Claims
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AI Technical Summary

Problems solved by technology

Although the CDD model satisfies the principle of visual connectivity and has a good repair effect on small-scale damaged images, it requires a large amount of calculation for damaged areas with complex textures, and there is a ladder effect.
The main problems of the existing technology are su

Method used

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  • Image restoration method based on curvature driven diffusion
  • Image restoration method based on curvature driven diffusion
  • Image restoration method based on curvature driven diffusion

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Embodiment Construction

[0031] Discretization steps of the model of the embodiment of the present invention:

[0032] The iterative formula for ,in is the time step, The corresponding discrete formula is , h is the spatial step along the horizontal and vertical directions.

[0033] use as figure 1 The half-point central difference method shown calculates the two formulas after discretization: set point is the point to be repaired, and its corresponding eight neighbor points are W N , W, W S , S, E S , E, E N and N. First, calculate the points to be repaired and the middle position point of the surrounding four neighbor points N, W, S, E n , w , s , e , and further calculate the corresponding . The specific calculation process is as follows (in points example):

[0034] (1)

[0035] and ,in,

[0036] , (2)

[0037] (3)

[0038] Similarly, it can be calculated in turn .

[0039] Specific steps are as follows

[0040] Step 1. Initi...

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Abstract

The invention discloses an image restoration method based on curvature-driven diffusion. A nonnegative, smooth and monotonically decreasing guiding function g(s) is introduced through a nonlinear diffusion term portion of a curvature driven diffusion (CDD) model, a self-adaptive CDD model is designed, wherein g(0) is equal to 1, a parameter s is a gradient module value, m is a regulatory factor of a margin guiding function decreasing speed, k is a threshold parameter, and median is mean value operation. The guiding function g(s) changes with change of the parameter s, the diffusion factor changes, and therefore restoration intensity self-adaptive control of an image smooth area and a texture and margin area is achieved. The self-adaptive model is better than a total variation (TV) model and the CDD model when a large scale damaged area is restored, image margin and detail information can be kept well, and vision effect is good.

Description

technical field [0001] The invention belongs to the field of digital image processing, and in particular relates to an image restoration method based on curvature-driven diffusion that can protect small but smooth isoluminance lines, retain image edges and detail information, have good restoration effect and high calculation efficiency. Background technique [0002] In recent years, with the continuous development of digital media technology, image restoration technology has been widely used, such as the protection of cultural relics and old photos, the restoration of image lossy compression, the error concealment of images and videos after network transmission, and the redundancy in images. Removal of remaining objects, etc. However, digital image restoration is a pathological problem because the original information has been destroyed and there is no standard image as a reference. Among the existing restoration methods, image restoration based on partial differential equa...

Claims

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Application Information

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IPC IPC(8): G06T5/00
Inventor 王相海宋传鸣王爽艾新楠
Owner LIAONING NORMAL UNIVERSITY
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