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Alpha穩(wěn)態(tài)噪聲下基于Meridian范數(shù)的全變分圖像去噪算法

楊真真,  楊震,  李雷,  金正猛

楊真真, 楊震, 李雷, 金正猛. Alpha穩(wěn)態(tài)噪聲下基于Meridian范數(shù)的全變分圖像去噪算法[J]. 電子與信息學(xué)報(bào), 2017, 39(5): 1109-1115. doi: 10.11999/JEIT160657
引用本文: 楊真真, 楊震, 李雷, 金正猛. Alpha穩(wěn)態(tài)噪聲下基于Meridian范數(shù)的全變分圖像去噪算法[J]. 電子與信息學(xué)報(bào), 2017, 39(5): 1109-1115. doi: 10.11999/JEIT160657
YANG Zhenzhen, YANG Zhen, LI Lei, JIN Zhengmeng. A Total Variational Approach Based on Meridian Norm for Restoring Noisy Images with Alpha-stable Noise[J]. Journal of Electronics & Information Technology, 2017, 39(5): 1109-1115. doi: 10.11999/JEIT160657
Citation: YANG Zhenzhen, YANG Zhen, LI Lei, JIN Zhengmeng. A Total Variational Approach Based on Meridian Norm for Restoring Noisy Images with Alpha-stable Noise[J]. Journal of Electronics & Information Technology, 2017, 39(5): 1109-1115. doi: 10.11999/JEIT160657

Alpha穩(wěn)態(tài)噪聲下基于Meridian范數(shù)的全變分圖像去噪算法

doi: 10.11999/JEIT160657 cstr: 32379.14.JEIT160657
  • 2.

    (南京郵電大學(xué)視覺(jué)認(rèn)知計(jì)算與應(yīng)用研究中心 南京 210023) ②(南京郵電大學(xué)寬帶無(wú)線(xiàn)通信與傳感網(wǎng)技術(shù)教育部重點(diǎn)實(shí)驗(yàn)室 南京 210003)

基金項(xiàng)目: 

國(guó)家自然科學(xué)基金(61501251, 61271335, 61271240)，江蘇省自然科學(xué)基金項(xiàng)目(BK20140891)，南京郵電大學(xué)引進(jìn)人才科研啟動(dòng)基金資助項(xiàng)目(NY214191)

A Total Variational Approach Based on Meridian Norm for Restoring Noisy Images with Alpha-stable Noise

  • 2.

    (Center for Visual Cognitive Computation and Application, Nanjing University of Posts and Telecommunications, Nanjing 210023, China)

Funds: 

The National Natural Science Foundation of China (61501251, 61271335, 61271240), The Natural Science Foundation of Jiangsu Province (BK20140891), The Science Foundation of Nanjing University of Posts and Telecommunications (NY214191)

  • 摘要: 在實(shí)際應(yīng)用中，噪聲不可避免，因此，圖像去噪一直是圖像處理領(lǐng)域研究的重點(diǎn)，并且近年來(lái)受到越來(lái)越多的研究者的青睞。該文首先基于Meridian分布和全變分(Total Variational, TV)的統(tǒng)計(jì)特性，提出一種全變分模型來(lái)復(fù)原alpha穩(wěn)態(tài)噪聲環(huán)境下的含噪聲圖像。此外，為了保證模型解的唯一性，對(duì)提出的全變分模型添加了一個(gè)二次懲罰項(xiàng)，得到一個(gè)嚴(yán)格凸的全變分模型，然后，使用原始-對(duì)偶算法對(duì)提出的全變分模型進(jìn)行求解，并證明了該算法的收斂性。最后，進(jìn)行了仿真實(shí)驗(yàn)，并對(duì)實(shí)驗(yàn)結(jié)果進(jìn)行了分析，實(shí)驗(yàn)結(jié)果驗(yàn)證了提出模型的可行性與有效性。
    Abstract: In actual applications, noises may inevitably exist, and thus to study the denoising method for images is great significant task in image processing filed that attracts much attention in recent years. In this paper, based on the statistical property of Meridian distributed and the Total Variational (TV), a total variational method is proposed for restoring images degraded by alpha-stable noise. Besides, in order to obtain a strictly convex model, a quadratic penalty term is added, which guarantees the uniqueness of the solution. For solving the novel convex variational model, a primal-dual algorithm is employed to solve the above model, and the convergence of the algorithm is proved. The experimental results demonstrate that the feasibility and effectiveness of the proposed model for the noisy images with alpha-stable noise.
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出版歷程
  • 收稿日期:  2016-06-21
  • 修回日期:  2017-01-03
  • 刊出日期:  2017-05-19

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