Efficiency Measurement of Various Denoise Techniques for Moving Object Detection Using Aerial Images

被引:0
作者
Mahayuddin, Zainal Rasyid [1 ]
Saif, A. F. M. Saifuddin [1 ]
Prabuwono, Anton Satria [2 ]
机构
[1] Univ Kebangsaan Malaysia, Fac Informat Sci & Technol, Ukm Bangi 43600, Selangor De, Malaysia
[2] King Abdulaziz Univ, Fac Comp & Informat Technol, Rabigh 21911, Saudi Arabia
来源
5TH INTERNATIONAL CONFERENCE ON ELECTRICAL ENGINEERING AND INFORMATICS 2015 | 2015年
关键词
Motion; Moving object; Computer vision; SEGMENTATION;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Noise reduction from aerial images is considered an image restoration mechanism in which it attempts to recover image from a degraded image. Denoising image is considered as the key factor for minimizing the functionality for piecewise smooth image intensity. Efficiency of various denoising techniques depends on frame rate and finally computation time for overall object detection mechanism. Moving object detection is the first step of image denoising as well as object detection. This technique uses segmentation, motion detection and feature extraction technique. The main goal of this paper is to compare various noise reduction techniques incorporated with various moving object detection methods along with various features like edges and corners based detection. Experimentation was done based on two parameters frame rate and computation time which initiate to choose the best denoising method for moving object detection.
引用
收藏
页码:161 / 165
页数:5
相关论文
共 13 条
  • [1] [Anonymous], P IEEE INT C IM PROC
  • [2] High accuracy optical flow estimation based on a theory for warping
    Brox, T
    Bruhn, A
    Papenberg, N
    Weickert, J
    [J]. COMPUTER VISION - ECCV 2004, PT 4, 2004, 2034 : 25 - 36
  • [3] Variational optical flow computation in real time
    Bruhn, A
    Weickert, J
    Feddern, C
    Kohlberger, T
    Schnörr, C
    [J]. IEEE TRANSACTIONS ON IMAGE PROCESSING, 2005, 14 (05) : 608 - 615
  • [4] De Vylder J., 2009, 16 IEEE ICDSP 2009, P1
  • [5] Guo YD, 2007, LECT NOTES COMPUT SC, V4781, P205
  • [6] Wavelet domain image denoising by thresholding and Wiener filtering
    Kazubek, M
    [J]. IEEE SIGNAL PROCESSING LETTERS, 2003, 10 (11) : 324 - 326
  • [7] A multigrid approach for hierarchical motion estimation
    Memin, E
    Perez, P
    [J]. SIXTH INTERNATIONAL CONFERENCE ON COMPUTER VISION, 1998, : 933 - 938
  • [8] ROBUST MULTIRESOLUTION ESTIMATION OF PARAMETRIC MOTION MODELS
    ODOBEZ, JM
    BOUTHEMY, P
    [J]. JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION, 1995, 6 (04) : 348 - 365
  • [9] Direct incremental model-based image motion segmentation for video analysis
    Odobez, JM
    Bouthemy, P
    [J]. SIGNAL PROCESSING, 1998, 66 (02) : 143 - 155
  • [10] Geodesic active contours and level sets for the detection and tracking of moving objects
    Paragios, N
    Deriche, R
    [J]. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2000, 22 (03) : 266 - 280