实时视频流缩放系统设计
[1] 吴以凯.基于FPGA的视频缩放的设计与实现[D].镇江: 江苏大学, 2017.
WU Y K.Design and implementation of video scaling based on FPGA [D]. Zhenjiang: Jiangsu University, 2017. (in Chinese)
[2] RETTKOWSKI J, BOUTROS A, GHRINGER D. HW/SW co-design of the HOG algorithm on a Xilinx Zynq SoC [J]. Journal of Parallel and Distributed Computing, 2017, 109: 50-62.
[3] KRYJAK T, KOMORKIEWICZ M, GORGON M. Real-time hardware-software embedded vision system for ITS smart camera implemented inZynq SoC [J]. Journal of Real-Time Image Processing, 2018, 15(1): 123-159.
[4] SENOUCI B, CHARFI I, HEYRMAN B,et al. Fast prototyping of a SoC-based smart-camera: a real-time fall detection case study [J]. Journal of Real-Time Image Processing, 2016, 12(4): 649-662.
[5] SVETEK A, BLAKE M, HERMIDA M C, et al. The calorimeter trigger processor card: the next generation of high speed algorithmic data processing at CMS [J]. Journal of Instrumentation, 2016, 11(2): C02011.
[6] 吴以凯, 喻金华, 肖铁军.基于FPGA的视频缩放设计与实现[J].软件导刊, 2017, 16(8): 83-85.
WU Y K, YU J H, XIAO T J. Design and implementation of video scaling based on FPGA [J].Software Guide, 2017, 16(8): 83-85. (in Chinese)
[7] 陈志杰, 凌朝东, 魏腾雄.双三次卷积模板插值算法的FPGA实现[J].液晶与显示, 2014, 29(1): 71-76.
[8] 王健, 于鸣, 任洪娥.一种用于图像拼接的改进ORB算法[J].液晶与显示, 2018, 33(6): 520-527.
[9] 王平, 全吉成, 赵柏宇.基于双线性插值的图像缩放在GPU上的实现[J].微电子学与计算机, 2016, 33(11): 129-132.
WANG P, QUAN J C, ZHAO B Y. Realization of image zooming in GPU based on bilinear interpolation [J]. Microelectronics & Computer, 2016, 33(11): 129-132. (in Chinese)
[10] 冉峰, 李天, 季渊, 等.基于FPGA的图像缩放算法设计[J].光电子技术, 2017, 37(1): 21-26.
[11] 岳鑫, 肖晨.基于奇异值分解和双三次插值的图像缩放算法改进[J].西安邮电大学学报, 2018, 23(4): 72-77.
YUE X, XIAO C. Improvement of imagescaling algorithm based on singular value decomposition and bicubic interpolation [J]. Journal of Xi'an University of Posts and Telecommunications, 2018, 23(4): 72-77. (in Chinese)
[12] 余成波, 李彩虹, 曾亮.K-means指纹定位的优化算法[J].电子技术应用, 2018, 44(2): 70-74.
YU C B, LI C H, ZENG L.Optimization algorithm of K-means fingerprint location [J]. Application of Electronic Technique, 2018, 44(2): 70-74. (in Chinese)
[13] KOOKARINRAT P, TEMTANAPAT Y. Analysis of range-based key properties for sharded cluster of MongoDB [C]//Proceedings of the 2015 2nd International Conference on Information Science and Security. Seoul, South Korea: IEEE, 2015: 1-4.
[14] KANG Y S, PARK I H, RHEE J,et al. MongoDB-based repository design for IoT-generated RFID/sensor big data [J]. IEEE Sensors Journal, 2016, 16(2): 485-497.
[15] CAI W J, XU Z H, LI Z Q. A high performance surf image feature detecting system based on ZYNQ [C]//Proceedings of the 2017 2nd International Conference on Computer Engineering, Information Science and Internet Technology. 2017: 101-110.
[16] XILINX C.Xilinx Corporation 7 Series Devices Memory Interface Solutions (UG586) [M]. Philadelphia, USA: Xilinx Corporation, 2013.
[17] 刘珂.基于ZYNQ的高速图像采集处理平台设计与验证[D].济南: 山东大学, 2016.
LIU K.Design and verification of high speed image gathering and processing platform based on ZYNQ [D]. Ji’nan: Shandong University, 2016. (in Chinese)
严飞, 陆宝毅, 刘银萍, 刘卿卿, 陈伟. 实时视频流缩放系统设计[J]. 液晶与显示, 2019, 34(11): 1124. YAN Fei, LU Bao-yi, LIU Yin-ping, LIU Qing-qing, CHEN Wei. Design of real-time video stream scaling system[J]. Chinese Journal of Liquid Crystals and Displays, 2019, 34(11): 1124.