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融合相位一致性與二維主成分分析的視覺顯著性預(yù)測(cè)

徐威 唐振民

徐威, 唐振民. 融合相位一致性與二維主成分分析的視覺顯著性預(yù)測(cè)[J]. 電子與信息學(xué)報(bào), 2015, 37(9): 2089-2096. doi: 10.11999/JEIT141478
引用本文: 徐威, 唐振民. 融合相位一致性與二維主成分分析的視覺顯著性預(yù)測(cè)[J]. 電子與信息學(xué)報(bào), 2015, 37(9): 2089-2096. doi: 10.11999/JEIT141478
Xu Wei, Tang Zhen-min. Integrating Phase Congruency and Two-dimensional Principal Component Analysis for Visual Saliency Prediction[J]. Journal of Electronics & Information Technology, 2015, 37(9): 2089-2096. doi: 10.11999/JEIT141478
Citation: Xu Wei, Tang Zhen-min. Integrating Phase Congruency and Two-dimensional Principal Component Analysis for Visual Saliency Prediction[J]. Journal of Electronics & Information Technology, 2015, 37(9): 2089-2096. doi: 10.11999/JEIT141478

融合相位一致性與二維主成分分析的視覺顯著性預(yù)測(cè)

doi: 10.11999/JEIT141478
基金項(xiàng)目: 

國(guó)家自然科學(xué)基金(61473154)

Integrating Phase Congruency and Two-dimensional Principal Component Analysis for Visual Saliency Prediction

  • 摘要: 為了更加有效地預(yù)測(cè)圖像中吸引視覺注意的關(guān)鍵區(qū)域,該文提出一種融合相位一致性與2維主成分分析(2DPCA)的顯著性方法。該方法不同于傳統(tǒng)的利用相位譜的方式,而是提出采用相位一致性(PC)獲取圖像中重要的特征點(diǎn)和邊緣信息,經(jīng)快速漂移超像素優(yōu)化后,融合局部和全局顏色對(duì)比度,生成低層特征顯著圖。接著提出利用2DPCA提取圖像塊的主成分后,計(jì)算主成分空間中圖像塊的局部和全局可區(qū)分性,得到模式顯著圖。最后,通過(guò)空間離散度度量分配合適的權(quán)重,使兩者融合,提取顯著性區(qū)域。在兩種人眼跟蹤數(shù)據(jù)庫(kù)上與5種經(jīng)典算法的實(shí)驗(yàn)對(duì)比結(jié)果表明,該算法能更加準(zhǔn)確地預(yù)測(cè)人眼視覺關(guān)注點(diǎn)。
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出版歷程
  • 收稿日期:  2014-11-24
  • 修回日期:  2015-03-11
  • 刊出日期:  2015-09-19

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