﻿ 基于非局部全变差模型和全局非零局部秩惩罚的图像去模糊 Image Deblurring Based on Non-Local Total Variation and Global Non-Zero Local Rank Penalty

Open Journal of Nature Science
Vol.03 No.02(2015), Article ID:15267,6 pages
10.12677/OJNS.2015.32003

Image Deblurring Based on Non-Local Total Variation and Global Non-Zero Local Rank Penalty

Jie Tang1, Jingman Xia1,2, Rong Liu1,2, Xingcan Li1, Wei Li2

1Chongqing Changpeng Industrial Group Co., Ltd., Chongqing

2Chongqing Huafu Industrial Co., Ltd, Chongqing

Email: 515742230@qq.com

Received: May 2nd, 2015; accepted: May 15th, 2015; published: May 22nd, 2015

ABSTRACT

The imaging and analysis module is an important part of automobile application system in the future, and clear images provide a reliable guarantee for the intelligent control system. However, due to the existing problems of imaging equipment hardware, the obtained images appear blurring. Therefore, in order to restore the clean images from the blur ones and bring convenience to the subsequent processing, this paper proposes an image deblurring method based on non-local total variation and global non-zero local rank penalty. The non-local total variation model is mainly used to restore the texture details of image, and the non-zero local rank penalty is mainly used to sharp the edge of the image. The proposed deblurring method in this paper has achieved better results on simulated images and real blurred image than other methods.

Keywords:Non-Local, Total Variation, Global Non-Zero Local Rank

1重庆长鹏实业(集团)有限公司，重庆

2重庆华福车船电子设备制造有限公司，重庆

Email: 515742230@qq.com

1. 引言

2. 基于非局部全变差模型的图像去模糊

2.1. 非局部全变差模型

(1)

(2)

(3)

2.2. 基于非局部全变差模型的图像去模糊

(4)

(5)

3. 局部秩

(6)

(7)

4. 所提出的方法

4.1. 非零局部秩惩罚约束项

(8)

(9)

4.2. 基于非局部全变差和非零局部秩惩罚的去模糊模型

(10)

5. 实验验证分析

5.1. 实验设置

5.2. 实验结果

Figure 1. Test images. Left is real clean image and right is real blur image

(a) (b) (c)

Figure 2. Recovery results of analog image: (a) Blur image; (b) Result of [13] ; (c) The proposed method

(a) (b) (c)

Figure 3. Recovery result of real blur image: (a) Real blur image; (b) Result of [13] ; (c) The proposed method

4. 结论

Image Deblurring Based on Non-Local Total Variation and Global Non-Zero Local Rank Penalty. 自然科学,02,12-18. doi: 10.12677/OJNS.2015.32003

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