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基于視覺顯著失真度的圖像質(zhì)量自適應(yīng)評(píng)價(jià)方法

豐明坤,  趙生妹,  邢超

豐明坤, 趙生妹, 邢超. 基于視覺顯著失真度的圖像質(zhì)量自適應(yīng)評(píng)價(jià)方法[J]. 電子與信息學(xué)報(bào), 2015, 37(9): 2062-2068. doi: 10.11999/JEIT141641
引用本文: 豐明坤, 趙生妹, 邢超. 基于視覺顯著失真度的圖像質(zhì)量自適應(yīng)評(píng)價(jià)方法[J]. 電子與信息學(xué)報(bào), 2015, 37(9): 2062-2068. doi: 10.11999/JEIT141641
Feng Ming-kun, Zhao Sheng-mei, Xing Chao. Image Quality Self-adaptive Assessment Based on Visual Salience Distortion[J]. Journal of Electronics & Information Technology, 2015, 37(9): 2062-2068. doi: 10.11999/JEIT141641
Citation: Feng Ming-kun, Zhao Sheng-mei, Xing Chao. Image Quality Self-adaptive Assessment Based on Visual Salience Distortion[J]. Journal of Electronics & Information Technology, 2015, 37(9): 2062-2068. doi: 10.11999/JEIT141641

基于視覺顯著失真度的圖像質(zhì)量自適應(yīng)評(píng)價(jià)方法

doi: 10.11999/JEIT141641
  • 2.

    (南京郵電大學(xué)信號(hào)處理與傳輸研究所 南京 210003) ②(浙江科技學(xué)院信息與電子工程學(xué)院 杭州 310023)

Image Quality Self-adaptive Assessment Based on Visual Salience Distortion

  • 2.

    (Institute of Signal Processing and Transmission, Nanjing University of Posts and Telecommunications,

  • 摘要: 針對(duì)結(jié)構(gòu)相似(SSIM)圖像質(zhì)量評(píng)價(jià)算法沒有考慮人眼視覺多通道性和對(duì)圖像高失真評(píng)價(jià)的不穩(wěn)定性，提出一種基于視覺顯著失真度的圖像質(zhì)量自適應(yīng)融合(VSAP)評(píng)價(jià)方法。該方法首先采用log-Gabor濾波提取圖像的高頻、中頻及低頻3層視覺特征，基于log-Gabor變換尺度和方向權(quán)重系數(shù)計(jì)算特征值的相似度；然后基于視覺閾值多分辨性迭加計(jì)算出特征值的失真度；最后，根據(jù)視覺失真度自適應(yīng)融合相似度評(píng)價(jià)與失真度評(píng)價(jià)獲得圖像質(zhì)量的最終客觀評(píng)價(jià)。實(shí)驗(yàn)結(jié)果表明，VSAP方法不但對(duì)圖像不同類型失真的客觀評(píng)價(jià)與主觀感知具有更高的相關(guān)性，而且3個(gè)主要指標(biāo)斯皮爾曼等級(jí)相關(guān)系數(shù)(SROCC)、曲線擬合相關(guān)系數(shù)(CC)和均方根誤差(RMSE)對(duì)圖像不同水平失真的整體評(píng)價(jià)性能更穩(wěn)定，明顯優(yōu)于其它評(píng)價(jià)方法。
    Abstract: The Structural SIMilarity (SSIM) algorithm of image quality assessment does not take into account the characteristics of multi-channel resolutions of human vision, it is also not consistent with subjective human evaluation for high level distortions. A Visual Salience Adaptive Pooling (VSAP) strategy of image quality assessment is proposed based on visual multi-scale and multi-orientation of log-Gabor transformation. Firstly, the visual characteristics of image on the high, medium, and low frequency are extracted by the log-Gabor transformation. Then the visual similarity scores based on visual scales and visual orientations of log-Gabor are calculated, accordingly, the visual distortion levels of image are calculated iteratively with the visual multi- resolution threshold. Finally, a strategy of image quality assessment is proposed with adaptive pooling similarity scores to distortion scores. The experimental results show that objective assessments of VSAP for different types of distortion hold higher correlation with subjective assessment. More importantly, the overall assessment performance of the Spearman Rank-Order Correlation Coefficient (SROCC), Correlation Coefficient (CC) and Root Mean Square Error (RMSE) for different levels of distortion is more consistent with subjective scores and superior to other methods.
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出版歷程
  • 收稿日期:  2014-12-25
  • 修回日期:  2015-04-01
  • 刊出日期:  2015-09-19

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