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基于局部最大梯度的無參考圖像質(zhì)量評價(jià)

蔣平,  張建州

蔣平, 張建州. 基于局部最大梯度的無參考圖像質(zhì)量評價(jià)[J]. 電子與信息學(xué)報(bào), 2015, 37(11): 2587-2593. doi: 10.11999/JEIT141447
引用本文: 蔣平, 張建州. 基于局部最大梯度的無參考圖像質(zhì)量評價(jià)[J]. 電子與信息學(xué)報(bào), 2015, 37(11): 2587-2593. doi: 10.11999/JEIT141447
Jiang Ping, Zhang Jian-zhou. No-reference Image Quality Assessment Based on Local Maximum Gradient[J]. Journal of Electronics & Information Technology, 2015, 37(11): 2587-2593. doi: 10.11999/JEIT141447
Citation: Jiang Ping, Zhang Jian-zhou. No-reference Image Quality Assessment Based on Local Maximum Gradient[J]. Journal of Electronics & Information Technology, 2015, 37(11): 2587-2593. doi: 10.11999/JEIT141447

基于局部最大梯度的無參考圖像質(zhì)量評價(jià)

doi: 10.11999/JEIT141447 cstr: 32379.14.JEIT141447
  • 2.

    (四川大學(xué)計(jì)算機(jī)學(xué)院 成都 610065) ②(榆林學(xué)院信息工程系 榆林 719000)

No-reference Image Quality Assessment Based on Local Maximum Gradient

  • 2.

    (Computer College, Sichuan University, Chengdu 610065, China)

  • 摘要: 圖像質(zhì)量評價(jià)在數(shù)字圖像處理中應(yīng)用廣泛，無參考圖像質(zhì)量評價(jià)更是近些年來的研究熱點(diǎn)。該文提出一種基于局部結(jié)構(gòu)的無參考圖像質(zhì)量評價(jià)方法，該方法首先利用局部梯度選擇強(qiáng)邊緣區(qū)域，然后通過強(qiáng)邊緣的信息來評價(jià)圖像的質(zhì)量。該方法的創(chuàng)新之處在于：基于局部最大梯度的像素點(diǎn)質(zhì)量評價(jià)；利用強(qiáng)邊緣點(diǎn)的局部質(zhì)量來估計(jì)全局圖像質(zhì)量。該方法可以同時(shí)評價(jià)噪聲圖像和模糊圖像，圖像失真越嚴(yán)重，該方法的評價(jià)分?jǐn)?shù)就越低。與圖像質(zhì)量評價(jià)數(shù)據(jù)庫的主觀評價(jià)結(jié)果比較表明，該文方法與主觀評價(jià)結(jié)果相關(guān)性很強(qiáng)，能很好地反映圖像質(zhì)量的視覺感知效果。
    Abstract: Image Quality Assessment (IQA) is widely used in digital image processing, and No Reference IQA (NR-IQA) has become the research focus recently. This paper proposes an NR-IQA method based on local structure, which chooses strong structure areas by using local gradients, and assesses the quality of image by utilizing the Maximum Local Gradients (MLG) of strong structure areas. The main novelties are: pixel,s quality assessment based on MLG; whole image quality based on strong edge points, quality. The proposed method can assess noise image and blur image at the same time, and the score of the proposed method is smaller when the distortion is more serious. The results show that the proposed no-reference method for the quality prediction of noise and blur images has a comparable performance to the leading metrics available in literature.
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出版歷程
  • 收稿日期:  2014-11-20
  • 修回日期:  2015-07-15
  • 刊出日期:  2015-11-19

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