光学 精密工程, 2016, 24 (1): 220, 网络出版: 2016-03-22   

纹理粗糙度在红外图像显著性检测中的应用

Application of texture coarseness in saliency detection of infrared image
作者单位
1 第二炮兵工程大学 控制工程系, 陕西 西安 710025
2 第二炮兵工程大学 士官学院, 山东 青州 262500
引用该论文

赵爱罡, 王宏力, 杨小冈, 陆敬辉, 姜伟. 纹理粗糙度在红外图像显著性检测中的应用[J]. 光学 精密工程, 2016, 24(1): 220.

ZHAO Ai-gang, WANG Hong-li, YANG Xiao-gang, LU Jing-hui, JIANG Wei. Application of texture coarseness in saliency detection of infrared image[J]. Optics and Precision Engineering, 2016, 24(1): 220.

参考文献

[1] 李一芒, 何昕, 魏仲慧, 等. 采用降维技术的红外目标检测与识别[J]. 光学 精密工程, 2013, 21(5): 1297-1303.

    LI Y M, HE X, WEI ZH H, et al.. Infrared target detection and recognition using dimension reduction technology [J]. Opt. Precision Eng., 2013, 21(5): 1297-1303. (in Chinese)

[2] 王建平, 李俊山, 杨亚威, 等. 基于红外成像的乙烯气体泄漏检测[J]. 液晶与显示, 2014, 29(4): 623-628.

    WANG J P, LI J SH, YANG Y W, et al.. Ethylene gas leaking detection based on infrared imaging [J]. Liquid Crystals and Displays, 2014, 29(4): 623-628. (in Chinese)

[3] 孙占久, 聂宏, 黄伟. 无人机红外辐射特性计算与分析[J]. 红外与激光工程, 2014, 43(4): 1037-1046.

    SUN ZH J, NIE H, HUANG W. Calculation and analysis on infrared radiation characteristics of UAV [J]. Infrared and Laser Engineering, 2014, 43(4): 1037-1046. (in Chinese)

[4] 赵宏伟, 陈霄, 刘萍萍, 等. 视觉显著目标的自适应分割[J]. 光学 精密工程, 2013, 21(2): 531-538.

    ZHAO H W, CHEN X, LIU P P, et al.. Adaptive segmentation for visual salient object [J]. Opt.Precision Eng., 2013, 21(2): 531-538. (in Chinese)

[5] 张来刚, 魏仲慧, 何昕, 等. 面向低纹理图像的快速立体匹配[J]. 液晶与显示, 2013, 28(3): 450-458.

    ZHANG L G, WEI ZH H, HE X, et al.. New stereo matching based edge extraction [J]. Liquid Crystals and Displays, 2013, 28(3): 450-458. (in Chinese)

[6] 邓丹, 吴谨, 朱磊, 等. 基于纹理抑制和连续性分布估计的显著性目标检测方法[J]. 液晶与显示, 2015, 30(1): 120-125.

    DENG D, WU J, ZHU L, et al.. Significant target detection method based on texture inhibition and continuous distribution estimation [J]. Liquid Crystals and Displays, 2015, 30(1): 120-125. (in Chinese)

[7] ITTI L, KOCH C, NIEBUR E. A model of saliency-based visual attention for rapid scene analysis [J]. IEEE Transactions on Pattern Analysis & Machine Intelligence, 1998, 20(11): 1254-1259.

[8] LIU T, YUAN Z, SUN J, et al.. Learning to detect a salient object [J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2011, 33(2): 353-367.

[9] ACHANTA R, HEMAMI S, ESTRADA F, et al.. Frequency-tuned salient region detection [C]. IEEE Conference on Computer Vision and Pattern Recognition, 2009: 1597-1604.

[10] HOU X, ZHANG L. Saliency detection: A spectral residual approach [C]. IEEE Conference on Computer Vision and Pattern Recognition, 2007: 1-8.

[11] RAO A R. A Taxonomy for Texture Description and Identification [M]. Springer Science & Business Media, 2012.

[12] FELZENSZWALB P, HUTTENLOCHER D P. Efficient graph-based image segmentation [J]. International Journal of Computer Vision, 2004, 59(2): 167-181.

[13] 肖钟捷, 刘用麟. 基于清晰图像先验知识的盲复原算法[J]. 红外与激光工程, 2015, 44(5): 1666-1672.

    XIAO ZH J, LIU Y L. Image blind restoration using priors of sharp images [J]. Infrared and Laser Engineering, 2015, 44(5): 1666-1672. (in Chinese)

[14] 金左轮, 韩静, 张毅, 等. 基于纹理显著性的微光图像目标检测[J]. 物理学报, 2014, 63(6): 69501.

    JIN Z L, HAN J, ZHANG Y, et al.. Low light level image target detection based on texture saliency [J]. Acta Phys. Sin., 2014, 63(6): 69501. (in Chinese)

[15] FAIRCHILD M D. Color Appearance Models [M]. New Jersey: John Wiley & Sons, 2013.

[16] CHENG M, MITRA N J, HUANG X, et al.. Global contrast based salient region detection [C]. IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2015, 37(3): 569-582.

赵爱罡, 王宏力, 杨小冈, 陆敬辉, 姜伟. 纹理粗糙度在红外图像显著性检测中的应用[J]. 光学 精密工程, 2016, 24(1): 220. ZHAO Ai-gang, WANG Hong-li, YANG Xiao-gang, LU Jing-hui, JIANG Wei. Application of texture coarseness in saliency detection of infrared image[J]. Optics and Precision Engineering, 2016, 24(1): 220.

本文已被 2 篇论文引用
被引统计数据来源于中国光学期刊网
引用该论文: TXT   |   EndNote

相关论文

加载中...

关于本站 Cookie 的使用提示

中国光学期刊网使用基于 cookie 的技术来更好地为您提供各项服务,点击此处了解我们的隐私策略。 如您需继续使用本网站,请您授权我们使用本地 cookie 来保存部分信息。
全站搜索
您最值得信赖的光电行业旗舰网络服务平台!