A Survey on Parallel Image Processing Studies Using CUDA Platform in GPU Programming

被引:0
作者
Aydin, Semra [1 ]
Samet, Refik [2 ]
Bay, Omer Faruk [3 ]
机构
[1] Gazi Univ, Bilisim Enstitusu, Ankara, Turkey
[2] Ankara Univ, Bilgisayar Muhendisligi Bolumu, Muhendislik Fak, Ankara, Turkey
[3] Gazi Univ, Elekt Elekt Muhendisligi Bolumu, Teknol Fak, Ankara, Turkey
来源
JOURNAL OF POLYTECHNIC-POLITEKNIK DERGISI | 2020年 / 23卷 / 03期
关键词
Image processing; parallel computing; GPU; CUDA; RECONSTRUCTION ALGORITHMS; SEGMENTATION ALGORITHM; PERFORMANCE EVALUATION; IMPLEMENTATION; REGISTRATION; ACCELERATION; MRI; EFFICIENCY; SPACE; MODEL;
D O I
暂无
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Image processing is used in a variety of fields. Image processing techniques need high processor performance due to increased image resolution day by day. Parallel processing techniques are used to satisfy the requirements related to high performance in real time image processing applications. Recently, GPU programming is one of the most commonly used and preferred methods in parallel processing. CUDA is the most popular platform in GPU programming. In this survey the studies where CUDA platform was used for image processing are presented and evaluated. The major purpose of this survey is to provide a comprehensive reference source for the starters or researchers involved in use of CUDA platform in GPU programming for image processing techniques. Studies using CUDA platform in GPU programming have been classified under 5 areas; image reconstruction, image enhancement, image segmentation, image registration and image classification. Advantages of using CUDA in GPU programming for image processing and issues to pay attention in applications have also been underlined.
引用
收藏
页码:737 / 754
页数:18
相关论文
共 50 条
  • [41] GPU processing for parallel image processing and real-time object recognition
    Vincent, Kevin
    Damien Nguyen
    Walker, Brian
    Lu, Thomas
    Chao, Tien-Hsin
    OPTICAL PATTERN RECOGNITION XXV, 2014, 9094
  • [42] Parallel UPGMA Algorithm on Graphics Processing Units Using CUDA
    Chen, Yu-Rong
    Hung, Che Lun
    Lin, Yu-Shiang
    Lin, Chun-Yuan
    Lee, Tien-Lin
    Lee, Kual-Zheng
    2012 IEEE 14TH INTERNATIONAL CONFERENCE ON HIGH PERFORMANCE COMPUTING AND COMMUNICATIONS & 2012 IEEE 9TH INTERNATIONAL CONFERENCE ON EMBEDDED SOFTWARE AND SYSTEMS (HPCC-ICESS), 2012, : 849 - 854
  • [43] Accelerating Rabin Karp on a Graphics Processing Unit (GPU) using Compute Unified Device Architecture (CUDA)
    Dayarathne, Nayomi
    Ragel, Roshan
    2014 7TH INTERNATIONAL CONFERENCE ON INFORMATION AND AUTOMATION FOR SUSTAINABILITY (ICIAFS), 2014,
  • [44] Performance Study of Satellite Image Processing on Graphics Processors Unit Using CUDA
    Jeong, In-Kyu
    Hong, Min-Gee
    Hahn, Kwang-Soo
    Choi, Joonsoo
    Kim, Choen
    KOREAN JOURNAL OF REMOTE SENSING, 2012, 28 (06) : 683 - 691
  • [45] Parallel programming for real-time image processing using computing agents
    Du, FL
    Izatt, A
    Bandera, C
    INTERNATIONAL CONFERENCE ON PARALLEL AND DISTRIBUTED PROCESSING TECHNIQUES AND APPLICATIONS, VOLS I-III, PROCEEDINGS, 1997, : 1505 - 1514
  • [46] Improving GPU Throughput through Parallel Execution Using Tensor Cores and CUDA Cores
    Ho, Khoa
    Zhao, Hui
    Jog, Adwait
    Mohanty, Saraju
    2022 IEEE COMPUTER SOCIETY ANNUAL SYMPOSIUM ON VLSI (ISVLSI 2022), 2022, : 223 - 228
  • [47] Software platform for parallel image processing and computer vision
    Taniguchi, R
    Makiyama, Y
    Tsuruta, N
    Yonemoto, S
    Arita, D
    PARALLEL AND DISTRIBUTED METHODS FOR IMAGE PROCESSING, 1997, 3166 : 2 - 10
  • [48] Parallel Image Dehazing Algorithm Based on GPU Using Fuzzy System and Hybird Evolution Algorithm
    Hung, Che-Lun
    Yan, Ren-You
    Wang, Hsiao-Hsi
    2016 17TH IEEE/ACIS INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING, ARTIFICIAL INTELLIGENCE, NETWORKING AND PARALLEL/DISTRIBUTED COMPUTING (SNPD), 2016, : 581 - 583
  • [49] Image Autoregressive Interpolation Model Using GPU-Parallel Optimization
    Wu, Jiaji
    Deng, Long
    Jeon, Gwanggil
    IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2018, 14 (02) : 426 - 436
  • [50] GSWO: A programming model for GPU-enabled parallelization of sliding window operations in image processing
    Yang, Po
    Clapworthy, Gordon
    Dong, Feng
    Codreanu, Valeriu
    Williams, David
    Liu, Baoquan
    Roerdink, Jos B. T. M.
    Deng, Zhikun
    SIGNAL PROCESSING-IMAGE COMMUNICATION, 2016, 47 : 332 - 345