WiME分布式无线复眼平台开发及提高分辨率的研究
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摘要
本文在研究现有无线传感器网络节点硬件平台特点的基础上，设计并实现了一种利用高性能ARM7处理器，支持IEEE 802．15．4协议的CC2420芯片和三维振动，温度等多种传感器搭建的新型无线传感器节点硬件平台OpenWSN。OpenWSN能够承担图像采集与传输、汇聚节点等对性能要求更高的应用，可与目前基于MCU方式的节点形成良好的互补。设计遵循了节点的标准化、微型化，低功耗和扩展性等原则。对该节点的测试表明该方案较好地实现了上述目标，因此它可以成为研究人员选用无线传感器网络平台的理想高端选择。
目前，该传感器网络平台应用在智能环境中的机器人导航研究中，每个传感器节点携带一个低分辨率摄像头以感知周边环境及其变化，覆盖广大面积的多套节点将借助无线通信联合工作，提供针对环境的较完备信息并可支持在网处理。节点设计中引入了FPGA芯片以硬件加速方式支持快速图像处理。FPGA+摄像头+OpenWSN称为WiME。
另外，论文还研究并提出了一种利用多个低分辨率图像以提高场景图像分辨率的方法。该方法通过模板获得图像间的单应矩阵，然后通过图像间的单应矩阵将图像映射到另一图像后，将不规则图像样本点以一定的方法进行不规则数据插值。该方法将为智能环境中的机器人及其导航提供可信的环境信息。
This paper proposes and implements a new open research platform of Wireless sensor networks (WSN) named OpenWSN. The scheme utilizes microcontroller of ARM family, wireless RF transceiver accorded with 802.15.4 specification, three dimension vibration sensor, temperature sensor and etc. Larger sized than Telos, OpenWSN has higher processing capability than current pervasive research hardware like Gains, Mica and Telos. OpenWSN can bear higher performance application, such as image data collection and pan coordinator, thus preferably complement current MCU scheme. OpenWSN follows the principle of standardization, miniature low energy consumption and expansibility. Test of the node shows that the implementation achieves the goal preferably and is an ideal choice of wireless sensor network platform for researchers.
At present, the platform of wireless sensor network is used in robot navigation directed by intelligent environment. Every node carries a low resolution camera to perceive environment and its modification. Covering vast area, a great many nodes cooperate in wireless communication mode and provide enough information about environment and also network process. The node introduces FPGA to support fast image process by hardware acceleration mode. Camera, FPGA and OpenWSN is called WiME.
In addition, the paper proposes one approach to enhance image resolution by a series low resolution images got by low resolution cameras. The approach is based on homography between two planes calculated by image template and the method maps one image into another image and then does interpolation under scatter data to achieve resolution enhancement.
目前，该传感器网络平台应用在智能环境中的机器人导航研究中，每个传感器节点携带一个低分辨率摄像头以感知周边环境及其变化，覆盖广大面积的多套节点将借助无线通信联合工作，提供针对环境的较完备信息并可支持在网处理。节点设计中引入了FPGA芯片以硬件加速方式支持快速图像处理。FPGA+摄像头+OpenWSN称为WiME。
另外，论文还研究并提出了一种利用多个低分辨率图像以提高场景图像分辨率的方法。该方法通过模板获得图像间的单应矩阵，然后通过图像间的单应矩阵将图像映射到另一图像后，将不规则图像样本点以一定的方法进行不规则数据插值。该方法将为智能环境中的机器人及其导航提供可信的环境信息。
This paper proposes and implements a new open research platform of Wireless sensor networks (WSN) named OpenWSN. The scheme utilizes microcontroller of ARM family, wireless RF transceiver accorded with 802.15.4 specification, three dimension vibration sensor, temperature sensor and etc. Larger sized than Telos, OpenWSN has higher processing capability than current pervasive research hardware like Gains, Mica and Telos. OpenWSN can bear higher performance application, such as image data collection and pan coordinator, thus preferably complement current MCU scheme. OpenWSN follows the principle of standardization, miniature low energy consumption and expansibility. Test of the node shows that the implementation achieves the goal preferably and is an ideal choice of wireless sensor network platform for researchers.
At present, the platform of wireless sensor network is used in robot navigation directed by intelligent environment. Every node carries a low resolution camera to perceive environment and its modification. Covering vast area, a great many nodes cooperate in wireless communication mode and provide enough information about environment and also network process. The node introduces FPGA to support fast image process by hardware acceleration mode. Camera, FPGA and OpenWSN is called WiME.
In addition, the paper proposes one approach to enhance image resolution by a series low resolution images got by low resolution cameras. The approach is based on homography between two planes calculated by image template and the method maps one image into another image and then does interpolation under scatter data to achieve resolution enhancement.
引文
[1] 孙利民，李建中，陈渝，等．无线传感器网络[M]．北京：清华大学出版社，2005．5．
[2] 无线传感器网络和RHD技术开始走向融合．http://www.eetchina.com/ART_8800377139_617687_d28eb227.HTM
[3] Emerson Uses Dust Networks~(TM) WSN Products in New Smart Wireless Solutions for Mainstream Manufacturing. http://www.onworld.com/html/newsdustemerson.htm
[4] Wireless Sensor Network Deployments with Fortune 500 Companies Demonstrate Crossbow's Market Leadership. Business Wire Date: 12/5/2005
[5] "Center for future health"-smart medical home university of Rochester. www.futurehealth.rochester.edu/smart%5fhome/
[6] 陈兴武；蒋新华；邹复民；王桐森，基于传感器网络的城市智能运输系统的构建，信息与控制[J]，2006．01．
[7] IEEE Standards 802.15.4~(TM)-2003 http://www.ieee802.org/15/pub/TG4.html
[8] Chipcon Corporation, CC2420 Datasheet (rev 1.3), http://www.chipcon.com/files/CC2420_Data_Sheet_1_3.pdf
[9] DS18B20 Datasheet. http://datasheets.maxim-ic.com/en/ds/DS18B20.pdf
[10] MCP6S26 Datasheet. http://ww1.microchip.com/downloads/en/DeviceDoc/21117a.pdf
[11] DS2401 Datasheet. http://www.maxim-ic.com.cn/pdfserv/cn/ds/DS2401_cn.pdf
[12] A. Rosenfeld and A.C. Kak, Digital Picture Processing, 2nd Ed., vol. 1, Academic Press, New York, 1982.
[13] J.Canny, "A computational approach to edge detection", IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 8, no. 6, pp. 679-698, Nov. 1986.
[14] David Liebowitz, Andrew Zisserman. Metric Rectification for Perspective Images of Planes [A]. Proc IEEE Conference on Computer Vision and Pattern Recognition [C]. June 1998. 482-488.
[15] F.Klein. Elementary Mathematics from an Advanced Standpoint. Macmillan, New York,1939
[16] EVS100K Datasheet, version 1.6. http://www.elecvision.com
[17] Julez, B., "A Method of Coding TV Signals Based on Edge Detection," Bell System Tech. (38), No.4, July 1959, pp. 1001-1020. Compression, Video. Television.
[18] OlmaG, MagliE. All-integer Hough transform: Performance evaluation. A. Image Processing, International Conference C. 2001, 338～341
[19] Galambos C, Kittler J, Matas J. Gradient based progressive probabilistic Hough transform. A.IEEE Proceedings of Image Signal Process. C. 2001. 158-165
[20] Galambos C, Kittler J, Matas J. Using gradient information to enhance the progressive probabilistic Hough transforms. Proceedings of Pattern Recognition. C.2000.560～563
[21] R.Y.Tsai and T.S.Huang. Multiframe image restoration and registration. In R.Y.Tsai and T.S.Huang, editors, Advances in Computer Vision and Image Processing, volume1, p317-339. JAI Press Inc.1984.
[22] S P Kim, N K Bose, H M Valenzuela. Recursive reconstruction of high resolution image from noisy under sampled multiframes J.IEEE Trans.onASSP, 1990, 38 6:1013-1027.
[23] Assaf Zomet, Shmuel Peleg. Super-Resolution from Multiple Images having Arbitrary Mutual Motion, S. Chaudhud (Editor) , Super-Resolution Imaging, Kluwer Academic. 2001, September.
[24] R .R. Schultz and R. L. Stevenson. A Bayesian approach to image expansion for improved definition. IEEE Trans. Image Processing.1994, 3, pp.23 3-242
[25] R .R. Schultz and R .L. Stevenson. Extraction of high-resolution frames from video sequences. IEEE Trans. Image Processing.1996, 5, pp.996-1011.
[26] A .M. Tekalp, M.K. Ozkan, and M.I. Sezn, High-resolution image reconstruction from lower-resolution image sequences and space-vary image restoration, in Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing. 1992, 3, pp.169-172.
[27] 梅向明，刘增贤，王汇淳，王智秋，高等几何，高等教育出版社，1998．
[28] 刘饮圣，最小二乘问题计算方法。北京：北京工业大学出版社，1989．
[29] 徐士良。C常用算法程序集。第2版。北京：清华大学出版社，1996
[30] L.G.Roberts, Machine Perception of Three-Dimension Solids," in Optical and Electro-Optimal Information Processing, J.t. Tippett, et al., Ed. Cambridge, MA: MIT Press, 1965，99-159-197
[31] 赵春晖．现代图像处理技术及Matlab实现[M]．北京：人民邮电出版社，2001．
[32] EVS100K Datasheet, version 1.6. http://www.elecvision.com
[33] Canny J. A computational approach to edge detection. IEEE Transactions on Pattern Analysis and Machine Intelligence,1996,18, 1986,8:679～698
[34] Jain A.K. "Fundamentals of digital image processing", Englewood cliffs, N.J. USA: Prentice-Hall, 1989.
[35] 王世儒，王金金，冯有前，李彦民．计算方法．西安电子科技大学出版社，1997．1．
[36] Thomas: M. Lehmannn. Survey: Interpolation Methods in Medical Image Processing. IEEE Transactions on Medical Imaging.1999, 18(11) pp. 1049-1075.
[37] ROBERT. G. KEYS. Cubic Convolution Interpolation for Digital Image Process, IEEE Trans. on ASSP, 1981, Dec. Vol. ASSP-29, No.6
[38] HSIEH S. Hou, Harry C. Andrews. Cubic splines for image interpolation and digital filtering [J].IEEE Trans Acoustics Speech Signal processing, 1978,26
[39] F351 H. Ur and D. from Gross. Improved Resolution Sub-pixel Shifted Pictures.54, pp. 181-186. 1992, CVGIP: Graph, Models, Image Processing.
[40] Mads Nielesen, Luc Florack ,and Rachid Deriche, "Regnlarization, Scale-Space, and Edge Detection Filters,"
[41] 程正兴，《小波分析算法与应用》，西安交通常大学出版社，1997
[42] 邱力为，宋子善，沈为群《直线参数检测的快速哈夫变换》，北京航空航天大学学报[J]，2003年8月第29卷第8期
[43] Sean Bonnan, Robert Stevenson. Spatial resolution enhancement of low-resolution image sequences: a comprehensive review with directions for future research. PIE Visual Communications and Image Processing, 1999.
[44] Keren D, Peleg S, Brada R. Image Sequence Enhancement Using Sub pixel Displacements [A].Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern
[45] J. G. Semple, G. T. Kneebone, Algebraic Projective Geometry, Oxford University Press, 1952.
[46] Luong Q-T, Faugeras OD. The fundamental matrix: Theory, algorithms, and stability analysis. International Journal of Computer Vision, 1996,17(1):p43～76.
[47] B. C. Tom and A. K. Kataggelos. An Iterative Algorithm for Improroving the Resolution of Video Sequences. In SPIE YCIP, 1996, vol. 2727: 1430-1438
[48] 32. Lyvers E P, Mitchell O R. Subpixel measurements suing a moment based edge operator. IEEE Trans on PAMI, 1989, 11(12): 1293-1309
[49] C. Srinivas and M. D. Srinath, A stochastic model-based approach for simultaneous restoration of multiple miss-registered images, SPIE, 1990, Vol. 1360: 1416-142
[50] G. Ramponi, Warped Distance for space variant linear image interpolation, IEEE Trans, Image Processing, 1999, 8: 629-639
[51] S. Peleg, D. Keren, and L. Schweitzer, Improving image resolution by using sub pixel motion. Pattern Recognition Letters. 1987, 5(3), pp223-226.
[52] D. Shepard, "A Two Dimensional Interpolation Function for Irregularly Spaced Data," Proc. ACM 23rd Nat' 1 Conf., pp. 517-524,
[53] L. L. Schumaker, "Two-stage methods for fitting surfaces to scattered data in Quantities Approximation". R. Schaback and K. Scherer(eds), Lecture Notes 556, Springer, Berlin, 1976, 378-389.
[54] G. M. Nielson, "Scattered Data Modeling", IEEE Computer Graphics and Applications, vol. 13, no. 1, pp. 60-70, 1993.
[55] Duchon, J. "Interpolation des fonctions de deux variables suivanfle principede la flexion des plaques minces. "RAIRO Analyse Numerique 10: 5-12, 1976
[56] de Boor, C.; HSllig, K. "Bivariate box splines and smooth functions on a three direction mesh". J. Comput. Appl. Math. 9 (1983), no. 1, 13--28. 41A15 (65D07)
[57] de Boor, C. DeVote, R.; Hillig, K. "Approximation order from smooth bivariate PP functions". Approximation theory, Ⅳ (College Station Tex., 1983), 353--357, Academic Press, New York, 1983. 41A15
[58] A. Brandt Boundary-Value "Multi-Level Adaptive Solutions to Problems," Mathematics of Computation, vol. 31, no.138, pp. 333-390 1977.
[59] 崔锦泰．何天晓，王仁宏。 "Interpolation by bivariate linear splines", in Alfred Haar Memorial Conference, J. Szabados and K. Tandori, eds, North-Holland, Amsterdam, 1986, Pp-237-255
[60] D. R. Forsey, R. H. Barrels. "Hierarchical B-spline refinement." Computer Graphics, Volume 22, pages 205-212, Aug. 1988.
[61] 王国夫，孙尧，张海勋．杨传安．“基于节点插入原理的大规模散乱数据插值”．哈尔滨工程大学学报，Vol．22，No．Ⅰ Feb，2001．
[2] 无线传感器网络和RHD技术开始走向融合．http://www.eetchina.com/ART_8800377139_617687_d28eb227.HTM
[3] Emerson Uses Dust Networks~(TM) WSN Products in New Smart Wireless Solutions for Mainstream Manufacturing. http://www.onworld.com/html/newsdustemerson.htm
[4] Wireless Sensor Network Deployments with Fortune 500 Companies Demonstrate Crossbow's Market Leadership. Business Wire Date: 12/5/2005
[5] "Center for future health"-smart medical home university of Rochester. www.futurehealth.rochester.edu/smart%5fhome/
[6] 陈兴武；蒋新华；邹复民；王桐森，基于传感器网络的城市智能运输系统的构建，信息与控制[J]，2006．01．
[7] IEEE Standards 802.15.4~(TM)-2003 http://www.ieee802.org/15/pub/TG4.html
[8] Chipcon Corporation, CC2420 Datasheet (rev 1.3), http://www.chipcon.com/files/CC2420_Data_Sheet_1_3.pdf
[9] DS18B20 Datasheet. http://datasheets.maxim-ic.com/en/ds/DS18B20.pdf
[10] MCP6S26 Datasheet. http://ww1.microchip.com/downloads/en/DeviceDoc/21117a.pdf
[11] DS2401 Datasheet. http://www.maxim-ic.com.cn/pdfserv/cn/ds/DS2401_cn.pdf
[12] A. Rosenfeld and A.C. Kak, Digital Picture Processing, 2nd Ed., vol. 1, Academic Press, New York, 1982.
[13] J.Canny, "A computational approach to edge detection", IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 8, no. 6, pp. 679-698, Nov. 1986.
[14] David Liebowitz, Andrew Zisserman. Metric Rectification for Perspective Images of Planes [A]. Proc IEEE Conference on Computer Vision and Pattern Recognition [C]. June 1998. 482-488.
[15] F.Klein. Elementary Mathematics from an Advanced Standpoint. Macmillan, New York,1939
[16] EVS100K Datasheet, version 1.6. http://www.elecvision.com
[17] Julez, B., "A Method of Coding TV Signals Based on Edge Detection," Bell System Tech. (38), No.4, July 1959, pp. 1001-1020. Compression, Video. Television.
[18] OlmaG, MagliE. All-integer Hough transform: Performance evaluation. A. Image Processing, International Conference C. 2001, 338～341
[19] Galambos C, Kittler J, Matas J. Gradient based progressive probabilistic Hough transform. A.IEEE Proceedings of Image Signal Process. C. 2001. 158-165
[20] Galambos C, Kittler J, Matas J. Using gradient information to enhance the progressive probabilistic Hough transforms. Proceedings of Pattern Recognition. C.2000.560～563
[21] R.Y.Tsai and T.S.Huang. Multiframe image restoration and registration. In R.Y.Tsai and T.S.Huang, editors, Advances in Computer Vision and Image Processing, volume1, p317-339. JAI Press Inc.1984.
[22] S P Kim, N K Bose, H M Valenzuela. Recursive reconstruction of high resolution image from noisy under sampled multiframes J.IEEE Trans.onASSP, 1990, 38 6:1013-1027.
[23] Assaf Zomet, Shmuel Peleg. Super-Resolution from Multiple Images having Arbitrary Mutual Motion, S. Chaudhud (Editor) , Super-Resolution Imaging, Kluwer Academic. 2001, September.
[24] R .R. Schultz and R. L. Stevenson. A Bayesian approach to image expansion for improved definition. IEEE Trans. Image Processing.1994, 3, pp.23 3-242
[25] R .R. Schultz and R .L. Stevenson. Extraction of high-resolution frames from video sequences. IEEE Trans. Image Processing.1996, 5, pp.996-1011.
[26] A .M. Tekalp, M.K. Ozkan, and M.I. Sezn, High-resolution image reconstruction from lower-resolution image sequences and space-vary image restoration, in Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing. 1992, 3, pp.169-172.
[27] 梅向明，刘增贤，王汇淳，王智秋，高等几何，高等教育出版社，1998．
[28] 刘饮圣，最小二乘问题计算方法。北京：北京工业大学出版社，1989．
[29] 徐士良。C常用算法程序集。第2版。北京：清华大学出版社，1996
[30] L.G.Roberts, Machine Perception of Three-Dimension Solids," in Optical and Electro-Optimal Information Processing, J.t. Tippett, et al., Ed. Cambridge, MA: MIT Press, 1965，99-159-197
[31] 赵春晖．现代图像处理技术及Matlab实现[M]．北京：人民邮电出版社，2001．
[32] EVS100K Datasheet, version 1.6. http://www.elecvision.com
[33] Canny J. A computational approach to edge detection. IEEE Transactions on Pattern Analysis and Machine Intelligence,1996,18, 1986,8:679～698
[34] Jain A.K. "Fundamentals of digital image processing", Englewood cliffs, N.J. USA: Prentice-Hall, 1989.
[35] 王世儒，王金金，冯有前，李彦民．计算方法．西安电子科技大学出版社，1997．1．
[36] Thomas: M. Lehmannn. Survey: Interpolation Methods in Medical Image Processing. IEEE Transactions on Medical Imaging.1999, 18(11) pp. 1049-1075.
[37] ROBERT. G. KEYS. Cubic Convolution Interpolation for Digital Image Process, IEEE Trans. on ASSP, 1981, Dec. Vol. ASSP-29, No.6
[38] HSIEH S. Hou, Harry C. Andrews. Cubic splines for image interpolation and digital filtering [J].IEEE Trans Acoustics Speech Signal processing, 1978,26
[39] F351 H. Ur and D. from Gross. Improved Resolution Sub-pixel Shifted Pictures.54, pp. 181-186. 1992, CVGIP: Graph, Models, Image Processing.
[40] Mads Nielesen, Luc Florack ,and Rachid Deriche, "Regnlarization, Scale-Space, and Edge Detection Filters,"
[41] 程正兴，《小波分析算法与应用》，西安交通常大学出版社，1997
[42] 邱力为，宋子善，沈为群《直线参数检测的快速哈夫变换》，北京航空航天大学学报[J]，2003年8月第29卷第8期
[43] Sean Bonnan, Robert Stevenson. Spatial resolution enhancement of low-resolution image sequences: a comprehensive review with directions for future research. PIE Visual Communications and Image Processing, 1999.
[44] Keren D, Peleg S, Brada R. Image Sequence Enhancement Using Sub pixel Displacements [A].Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern
[45] J. G. Semple, G. T. Kneebone, Algebraic Projective Geometry, Oxford University Press, 1952.
[46] Luong Q-T, Faugeras OD. The fundamental matrix: Theory, algorithms, and stability analysis. International Journal of Computer Vision, 1996,17(1):p43～76.
[47] B. C. Tom and A. K. Kataggelos. An Iterative Algorithm for Improroving the Resolution of Video Sequences. In SPIE YCIP, 1996, vol. 2727: 1430-1438
[48] 32. Lyvers E P, Mitchell O R. Subpixel measurements suing a moment based edge operator. IEEE Trans on PAMI, 1989, 11(12): 1293-1309
[49] C. Srinivas and M. D. Srinath, A stochastic model-based approach for simultaneous restoration of multiple miss-registered images, SPIE, 1990, Vol. 1360: 1416-142
[50] G. Ramponi, Warped Distance for space variant linear image interpolation, IEEE Trans, Image Processing, 1999, 8: 629-639
[51] S. Peleg, D. Keren, and L. Schweitzer, Improving image resolution by using sub pixel motion. Pattern Recognition Letters. 1987, 5(3), pp223-226.
[52] D. Shepard, "A Two Dimensional Interpolation Function for Irregularly Spaced Data," Proc. ACM 23rd Nat' 1 Conf., pp. 517-524,
[53] L. L. Schumaker, "Two-stage methods for fitting surfaces to scattered data in Quantities Approximation". R. Schaback and K. Scherer(eds), Lecture Notes 556, Springer, Berlin, 1976, 378-389.
[54] G. M. Nielson, "Scattered Data Modeling", IEEE Computer Graphics and Applications, vol. 13, no. 1, pp. 60-70, 1993.
[55] Duchon, J. "Interpolation des fonctions de deux variables suivanfle principede la flexion des plaques minces. "RAIRO Analyse Numerique 10: 5-12, 1976
[56] de Boor, C.; HSllig, K. "Bivariate box splines and smooth functions on a three direction mesh". J. Comput. Appl. Math. 9 (1983), no. 1, 13--28. 41A15 (65D07)
[57] de Boor, C. DeVote, R.; Hillig, K. "Approximation order from smooth bivariate PP functions". Approximation theory, Ⅳ (College Station Tex., 1983), 353--357, Academic Press, New York, 1983. 41A15
[58] A. Brandt Boundary-Value "Multi-Level Adaptive Solutions to Problems," Mathematics of Computation, vol. 31, no.138, pp. 333-390 1977.
[59] 崔锦泰．何天晓，王仁宏。 "Interpolation by bivariate linear splines", in Alfred Haar Memorial Conference, J. Szabados and K. Tandori, eds, North-Holland, Amsterdam, 1986, Pp-237-255
[60] D. R. Forsey, R. H. Barrels. "Hierarchical B-spline refinement." Computer Graphics, Volume 22, pages 205-212, Aug. 1988.
[61] 王国夫，孙尧，张海勋．杨传安．“基于节点插入原理的大规模散乱数据插值”．哈尔滨工程大学学报，Vol．22，No．Ⅰ Feb，2001．