本文選題：圖像處理 + Meridian范數(shù)��； 參考：《電子與信息學報》2017年05期

【摘要】：在實際應用中,噪聲不可避免,因此,圖像去噪一直是圖像處理領域研究的重點,并且近年來受到越來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)計特性,提出一種全變分模型來復原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,對提出的全變分模型添加了一個二次懲罰項,得到一個嚴格凸的全變分模型,然后,使用原始-對偶算法對提出的全變分模型進行求解,并證明了該算法的收斂性。最后,進行了仿真實驗,并對實驗結果進行了分析,實驗結果驗證了提出模型的可行性與有效性。
[Abstract]:In practical application, noise is inevitable, so image denoising has been the focus of image processing research, and has been more and more popular in recent years. Based on the statistical properties of Meridian distribution and Total Variational TVs, a total variational model is proposed to restore noisy images in alpha stationary noise environment. In addition, in order to ensure the uniqueness of the solution of the model, a quadratic penalty term is added to the proposed total variational model, and a strictly convex total variational model is obtained. Then, the primal-dual algorithm is used to solve the proposed total variational model. The convergence of the algorithm is proved. Finally, the simulation experiment is carried out, and the experimental results are analyzed. The experimental results verify the feasibility and validity of the proposed model.
【作者單位】： 南京郵電大學視覺認知計算與應用研究中心;南京郵電大學寬帶無線通信與傳感網(wǎng)技術教育部重點實驗室;
【基金】：國家自然科學基金(61501251,61271335,61271240) 江蘇省自然科學基金項目(BK20140891) 南京郵電大學引進人才科研啟動基金資助項目(NY214191)~~
【分類號】：TP391.41
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本文編號：1876899