激光与光电子学进展, 2017, 54 (6): 061002, 网络出版: 2017-06-26   

灰度一致纹理图像的光参数估算方法

Estimation of Lighting Parameters for Uniform Texture Image
作者单位
1 鲁东大学信息与电气工程学院, 山东 烟台 264025
2 中国海洋大学信息科学与工程学院, 山东 青岛 266100
摘要
从单幅图像估算光照参数时未知条件太多,而采用多幅输入图像的方法估算光照参数,虽然精度较高,但增加了输入数据的复杂度。提出灰度一致图像的光参数估算方法,能够从输入的单幅图像准确地估算光照参数。该方法通过探测输入图像的最大亮度变化方向估算光照的方位角;通过检测输入图像与虚拟光环境下的随机纹理的相似性估算光照的翘角。对Photex纹理库中的24类图像(共142幅图像)进行了实验,实验结果表明,该算法对于表面灰度一致图像的光参数估算具有较高的准确率。
Abstract
Estimating lighting direction from a single input image requires too many unknown parameters, whereas although the accurate estimated lighting parameters from multiple input images can be obtained, the complexity of the input data is increased. The method for lighting parameters estimation of the uniform texture images is proposed. The proposed algorithm only utilizes one input image for estimating the lighting directions. By detecting the largest direction of the brightness changes of the input image, the azimuth angle of the light source can be estimated. The slant angle is estimated by detecting the similarity between the input image and the random texture with virtual lighting conditions. 24 kinds of texture images (142 images) in Photex database are studied experimentally. Experimental results show that the proposed approach is effective and robust in estimating the lighting parameters for the uniform texture images.
参考文献

[1] 张祺深, 周 雅, 胡晓明, 等. 基于三维点云匹配的手掌静脉识别[J]. 光学学报, 2015, 35(1): 0115005.

    Zhang Qishen, Zhou Ya, Hu Xiaoming, et al. Hand vein recognition based on three-dimensional point clouds matching[J]. Acta Optica Sinica, 2015, 35(1): 0115005.

[2] 宋鹏程, 文尚胜, 尚 俊, 等. 基于PWM的三基色LED的调光调色方法[J]. 光学学报, 2015, 35(2): 0223001.

    Song Pengcheng, Wen Shangsheng, Shang Jun, et al. A dimming method for RGB LED based on three channels′ PWM[J]. Acta Optica Sinica, 2015, 35(2): 0223001.

[3] Liszio S, Masuch M. Designing shared virtual reality gaming experiences in local multi-platform games[C]. 15th International Conference on Entertainment Computing, 2016: 235-240.

[4] Sun Y J, Jian M W, Zhang X F, et al. Reconstruction of normal and albedo of convex Lambertian objects by solving ambiguity matrices using SVD and optimization method[J]. Neurocomputing, 2016, 207: 95-104.

[5] 于之靖, 王韶彬. 改进PCA-SIFT算法的立体匹配系统[J]. 激光与光电子学进展, 2016, 53(3): 031501.

    Yu Zhijing, Wang Shaobin. Improved PCA-SIFT algorithm for matching stereo system[J]. Laser & Optoelectronics Progress, 2016, 53(3): 031501.

[6] Weber M, Cipolla R. A practical method for estimation of point light-sources[C]. Proceedings British Machine Vision Conference, 2001: 1-10.

[7] Peng B, Wang W, Dong J, et al. Improved 3D lighting environment estimation for image forgery detection[C]. 2015 IEEE International Workshop on Information Forensics and Security, 2015: 1-6.

[8] Tachikawa T, Hiura S, Sato K. Robust estimation of light directions and diffuse reflectance of known shape object[C]. Proceedings of Vision, Modeling, and Visualization Workshop, 2009: 37-44.

[9] Hara K, Nishino K,Ikeuchi K. Light source position and reflectance estimation from a single view without the distant illumination assumption[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2005, 27(4): 493-505.

[10] Li Y Z, Lin S, Lu H Q, et al. Multiple-cue illumination estimation in textured scenes[C]. Proceedings of 2003 IEEE International Conference on Computer Vision, 2003, 2: 1366.

[11] Baba M, Haruta K, Hiura S. Estimating lighting environments based on shadow area in an omni-directional image[C]. Proceedings of 2016 ACM SIGGRAPH, 2016: 88.

[12] Liu Y L, Qin X Y, Xu S H, et al. Light source estimation of outdoor scenes for mixed reality[J]. The Visual Computer, 2009, 25(5): 637-646.

[13] Vo M, Narasimhan S G, Sheikh Y. Separating texture and illumination for single-shot structured light reconstruction[C]. Proceedings of the 2014 IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2014: 433-440.

[14] Jiang Z S, Rezvankhah S, Siddiqi K. Light source estimation using Kinect[R]. Project Report, 2013.

[15] Koenderink J J, Pont S C. Irradiation direction from texture[J]. Journal of the Optical Society of America A, 2003, 20(10): 1875-1882.

[16] Varma M, Zisserman A. Estimating illumination direction from textured images[C]. Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004(1): 179-186.

[17] Ikeuchi K, Sato K. Determiningre flectance properties of an object using range and brightness images[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1991, 13(11): 1139-1153.

[18] Chantler M J, McGunnigle G. The response of texture features to illuminant rotation[C]. Proceedings of 15th International Conference on Pattern Recognition, 2000, 3: 943-946

[19] Chantler M, Petrou M, Penirsche A, et al. Classifying surface texture while simultaneously estimating illumination direction[J]. International Journal of Computer Vision, 2005, 62(1): 83-96.

[20] Dong J Y, Su L Y, Zhang Y, et al. Estimating illumination direction of three-dimensional surface texture based on active basis and Mojette transform[J]. Journal of Electronic Imaging, 2012, 21(1): 013023.

[21] Pineo D, Ware C. Data visualization optimization via computational modeling of perception[J]. IEEE Transactions on Visualization and Computer Graphics, 2012, 18(2): 309-320.

孙玉娟, 董军宇, 王增锋. 灰度一致纹理图像的光参数估算方法[J]. 激光与光电子学进展, 2017, 54(6): 061002. Sun Yujuan, Dong Junyu, Wang Zengfeng. Estimation of Lighting Parameters for Uniform Texture Image[J]. Laser & Optoelectronics Progress, 2017, 54(6): 061002.

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