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基于虛擬光學(xué)的視覺顯著目標(biāo)可控放大重建

陳家禎,  吳為民,  鄭子華,  葉鋒,  連桂仁,  許力

陳家禎, 吳為民, 鄭子華, 葉鋒, 連桂仁, 許力. 基于虛擬光學(xué)的視覺顯著目標(biāo)可控放大重建[J]. 電子與信息學(xué)報(bào), 2020, 42(5): 1209-1215. doi: 10.11999/JEIT190469
引用本文: 陳家禎, 吳為民, 鄭子華, 葉鋒, 連桂仁, 許力. 基于虛擬光學(xué)的視覺顯著目標(biāo)可控放大重建[J]. 電子與信息學(xué)報(bào), 2020, 42(5): 1209-1215. doi: 10.11999/JEIT190469
Jiazhen CHEN, Weimin WU, Zihua ZHENG, Feng YE, Guiren LIAN, Li XU. Controllable Magnification for Visual Saliency Object Based on Virtual Optics[J]. Journal of Electronics & Information Technology, 2020, 42(5): 1209-1215. doi: 10.11999/JEIT190469
Citation: Jiazhen CHEN, Weimin WU, Zihua ZHENG, Feng YE, Guiren LIAN, Li XU. Controllable Magnification for Visual Saliency Object Based on Virtual Optics[J]. Journal of Electronics & Information Technology, 2020, 42(5): 1209-1215. doi: 10.11999/JEIT190469

基于虛擬光學(xué)的視覺顯著目標(biāo)可控放大重建

doi: 10.11999/JEIT190469 cstr: 32379.14.JEIT190469
  • 1.

    福建師范大學(xué)數(shù)學(xué)與信息學(xué)院 ??福州 ??350007

  • 2.

    福建師范大學(xué)數(shù)字福建大數(shù)據(jù)安全技術(shù)研究所 ??福州 ??350007

  • 3.

    福建省船政交通職業(yè)學(xué)院信息工程系 ??福州 ??350007

基金項(xiàng)目: 福建省自然科學(xué)基金(2018J01779, 2017J01739)
詳細(xì)信息
    作者簡(jiǎn)介:

    陳家禎：女，1971年生，副教授，研究方向?yàn)樾盘?hào)與信息處理、信息安全

    吳為民：男，1970年生，副教授，研究方向?yàn)橛?jì)算機(jī)視覺、人工智能

    鄭子華：女，1976年生，副教授，研究方向?yàn)閿?shù)字圖像處理

    葉鋒：男，1978年生，副教授，研究方向?yàn)橐曨l圖像處理

    連桂仁：男，1963年生，副教授，研究方向?yàn)閿?shù)字圖像處理、電路與系統(tǒng)

    許力：男，1970年生，教授，研究方向?yàn)榫W(wǎng)絡(luò)與信息安全、智能信息處理

    通訊作者:

    葉鋒　yef279@sina.com

  • 中圖分類號(hào): TN911.73; TP391.41

Controllable Magnification for Visual Saliency Object Based on Virtual Optics

  • 1.

    College of Mathematics and Informatics, Fujian Normal University, Fuzhou 350007, China

  • 2.

    Digital Fujian Institute of Big Data Security Technology, Fujian Normal University, Fuzhou 350007, China

  • 3.

    Department of Information Engineering, Fujian Chuanzheng Communications college, Fuzhou 350007, China

Funds: The Natural Science Foundation of Fujian Province of China (2018J01779, 2017J01739)
  • 摘要:

    該文提出一種基于虛擬光學(xué)的視覺顯著目標(biāo)高分辨率可控放大重建方法。原始圖像放置于虛擬光路物平面，首先通過衍射逆計(jì)算獲得原始圖像在虛擬衍射面的光波信號(hào)，再對(duì)虛擬衍射面光波用球面波照射后作正向衍射計(jì)算，通過改變觀測(cè)平面位置可重建出不同放大率的原始圖像。仿真測(cè)試結(jié)果表明，與一般的插值放大方法相比，所獲得的放大后的圖像特別是在顯著性區(qū)域表示出良好的視覺感知效果。將包含人臉的低分辨率降質(zhì)圖像作為待重建信號(hào)，所重建人臉的顯著性區(qū)域如眼睛、鼻子等比一般重建方法更清晰。用水平集方法結(jié)合顯著圖分割出原始圖像中的局部顯著區(qū)域并作放大重建和輪廓提取，輪廓表現(xiàn)出良好的光滑性。

    Abstract:

    A high-resolution controllable magnification method for visual saliency object based on virtual optics is proposed in this paper. The original image is placed on the virtual object plane. Firstly, the diffractive wave of the original image on the virtual diffraction plane is obtained by inverse diffraction calculation, and then the forward diffraction calculation is carried out after the virtual diffraction wave is irradiated by spherical wave. The original images with different magnification can be reconstructed by changing the position of the observation plane. The simulation results show that compared with the general interpolation method, the magnified image shows a good visual perception effect, especially in the saliency region. When the degraded face image is used as the signal to be reconstructed, the significant areas such as eyes and nose are clearer than the general method. The local salient region in the original image is segmented by the level set method combined with salient map, and the magnification and contour extraction are performed. The contours show good smoothness.

    • HTML全文

  • 圖  1  數(shù)字圖像可控放大虛擬光路圖

    圖  2  元胞自動(dòng)機(jī)顯著性檢測(cè)算法流程圖

    圖  3  基于虛擬光學(xué)的放大重建

    圖  4  包含人物的場(chǎng)景及譜殘差方法計(jì)算得到的顯著圖

    圖  5  不同放大方法下眼睛部分的放大重建效果

    圖  6  眼睛區(qū)域的過零點(diǎn)檢測(cè)結(jié)果

    圖  7  降質(zhì)圖像及8倍放大重建

    圖  8  結(jié)合顯著圖與水平集方法的局部顯著目標(biāo)分割

    圖  9  局部顯著目標(biāo)放大4倍后的輪廓

    圖  10  部分目標(biāo)輪廓斜率及離散曲率比較

    表  1  放大重建像質(zhì)量指標(biāo)

    測(cè)試圖像NMSENLVESFM歸一化相關(guān)系數(shù)
    Mola0.10570.01570.00420.9977
    Barbara0.11060.01450.00190.9963
    Couple0.10450.00210.00220.9956
    平均值0.07690.01080.00270.9965
    下載: 導(dǎo)出CSV
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出版歷程
  • 收稿日期:  2019-06-25
  • 修回日期:  2019-10-30
  • 網(wǎng)絡(luò)出版日期:  2019-11-04
  • 刊出日期:  2020-06-04

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