Video compression quality metrics correlation with aided target recognition (ATR) applications

被引:1
|
作者
Grim, MH [1 ]
Szu, H [1 ]
机构
[1] USN, Ctr Surface Warfare, Dahlgren Lab, Dahlgren, VA 22448 USA
关键词
D O I
10.1117/1.482663
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Tactical battlefield surveillance systems will require the transmission of compressed video to utilize the limited communication bandwidth and data capacity of these systems. Any compression techniques used wilt result in some loss of information. If is important to assess the quality of the output video to determine its performance in aided target recognition applications. The traditional rate of distortion formula is shown by Mallet [S. Mallet, "Understanding wavelet image compression," Proc. SPIE Wavelet Apps. IV 3078, 74-93 (April 1997); "A theory for multiresolution signal decomposition: The wavelet representation," IEEE Trans. Pattern Anal. Mach. Intell. 11, 674-693 (1989)] to be inappropriate for wavelet compression in high compression ratios. The reason is that the histogram changes from atl gray scale to a concentration singularity near the origin of very low bit rate such that the discrete approximation of the density function of the histogram is no longer valid. Thus we cannot theoretically predict the distortion due to wavelet compression. Therefore we conduct an empirical investigation to evaluate the spatial and temporal effects of lossy wavelet compression and reconstruction on tactical infrared video. We quantify localized peak signal-to-noise ratio and feature persistence measure measurements and objective assessment techniques developed by the institute for Telecommunication Sciences, U.S. Department of commerce to assess video impairment based on quality measurements. We therefore measure video degradation rather than absolute video quality which is difficult to quantify. (C) 1998 SPIE and IS&T. [51017-9909(98)00704-1].
引用
收藏
页码:740 / 745
页数:6
相关论文
共 25 条
  • [1] Video compression quality metrics correlation with aided target recognition (ATR) applications
    Naval Surface Warfare Center, Dahlgren Laboratory, Dahlgren, VA 22448, United States
    不详
    不详
    不详
    不详
    不详
    不详
    [J]. J Electron Imaging, 4 (740-745):
  • [2] Comparison of video compression evaluation metrics for military applications
    Leachtenauer, JC
    [J]. HUMAN VISION AND ELECTRONIC IMAGING V, 2000, 3959 : 88 - 98
  • [3] Test patterns and quality metrics for digital video compression
    Fenimore, C
    Field, B
    VanDegrift, C
    [J]. HUMAN VISION AND ELECTRONIC IMAGING II, 1997, 3016 : 269 - 276
  • [4] Using video quality metrics for something other than compression
    Kokaram, Anil
    Kelly, Damien
    Inguva, Sasi
    Lin, Jessie
    Wang, Yilin
    Chen, Chao
    Birkbeck, Neil
    Covell, Michele
    Adsumilli, Balu
    Benting, Steve
    [J]. APPLICATIONS OF DIGITAL IMAGE PROCESSING XLI, 2018, 10752
  • [5] Video compression dataset and benchmark of learning-based video-quality metrics
    Antsiferova, Anastasia
    Lavrushkin, Sergey
    Smirnov, Maksim
    Gushchin, Alexander
    Vatolin, Dmitriy
    Kulikov, Dmitriy
    [J]. ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 35 (NEURIPS 2022), 2022,
  • [6] Objective image quality metrics for DCT-based video compression
    Oguz, H
    Faibish, A
    Faibish, S
    Cotter, G
    [J]. SMPTE JOURNAL, 2002, 111 (09): : 385 - 392
  • [7] Visual Saliency Aided High Dynamic Range (HDR) Video Quality Metrics
    Banitalebi-Dehkordi, Amin
    Azimi, Maryam
    Pourazad, Mahsa T.
    Nasiopoulos, Panos
    [J]. 2016 IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS WORKSHOPS (ICC), 2016, : 486 - 491
  • [8] Effcient video compression and improving quality of video in communication for computer endcoding applications
    Kumar, K. Siva
    Kumar, S. Sasi
    Kumar, N. Mohan
    [J]. COMPUTER COMMUNICATIONS, 2020, 153 : 152 - 158
  • [9] Survey of Recent Developments in Quality Assessment for Target Recognition Video
    Leszczuk, Mikolaj
    Dumke, Joel
    [J]. MULTIMEDIA COMMUNICATIONS, SERVICES AND SECURITY, MCSS 2013, 2013, 368 : 59 - 70
  • [10] On Evaluation of Video Quality Metrics: an HDR Dataset for Computer Graphics Applications
    Cadik, Martin
    Aydin, Tunc O.
    Myszkowski, Karol
    Seidel, Hans-Peter
    [J]. HUMAN VISION AND ELECTRONIC IMAGING XVI, 2011, 7865