An image sharpness metric for image processing applications using feedback

被引:0
|
作者
Lam, Eric P. [1 ,2 ]
Leddy, Christopher A. [2 ]
Nash, Stephen R. [2 ]
机构
[1] Thales Raytheon Syst, Batterfield Radar,1801 Hughes Dr, Fullerton, CA USA
[2] Raytheon Space & Airborne Syst, El Segundo, CA USA
关键词
image processing system; closed-loop system; sharpness; metric; edge; frame;
D O I
10.1117/12.719083
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
Some image processing applications require an image to meet a quality metric before performing processing on it. If an image is too degraded such that it is difficult or impossible to reconstruct, the input image may be discarded. When conditions do not exhibit time-invariant image degradations, it is necessary to determine how sharp an image is. In this paper, we present a metric that measures the relative sharpness with respect to a reference image frame. The reference image frame may be a previous input image or even an output frame from the image processor. The sharpness metric is based on analyzing edges. The assumption of this problem is that input images are similar to each other in terms of observation angle and time. Although the input images are similar, it cannot be assumed that all input images are the same, because they are collected at different time samples.
引用
收藏
页数:10
相关论文
共 50 条
  • [1] A sharpness metric implementation for image processing applications with feedback
    Lam, Eric P.
    [J]. ADVANCED SIGNAL PROCESSING ALGORITHMS, ARCHITECTURES, AND IMPLEMENTATIONS XVIII, 2008, 7074
  • [2] Aberration balancing using an image-sharpness metric
    Kazasidis, Orestis
    Verpoort, Sven
    Wittrock, Ulrich
    [J]. JOURNAL OF THE OPTICAL SOCIETY OF AMERICA A-OPTICS IMAGE SCIENCE AND VISION, 2019, 36 (08) : 1418 - 1422
  • [3] FUZZY METRIC SPACE AND APPLICATIONS IN IMAGE PROCESSING
    Ralevic, Nebojsa M.
    Paunovic, Marija
    Iricanin, Bratislav
    [J]. MATHEMATICA MONTISNIGRI, 2020, 48 : 103 - 117
  • [4] A NO REFERENCE OBJECTIVE COLOR IMAGE SHARPNESS METRIC
    Maalouf, Aldo
    Larabi, Mohamed-Chaker
    [J]. 18TH EUROPEAN SIGNAL PROCESSING CONFERENCE (EUSIPCO-2010), 2010, : 1019 - 1022
  • [5] OMNIDIRECTIONAL IMAGE PROCESSING USING GEODESIC METRIC
    Demonceaux, C.
    Vasseur, P.
    [J]. 2009 16TH IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING, VOLS 1-6, 2009, : 221 - 224
  • [6] IMAGE-PROCESSING SYSTEM USING INCOHERENT IMAGE FEEDBACK
    SATO, T
    SASAKI, K
    YAMAMOTO, R
    [J]. APPLIED OPTICS, 1978, 17 (05): : 717 - 720
  • [7] IMAGE SHARPNESS METRIC BASED ON MAXPOL CONVOLUTION KERNELS
    Hosseini, Mahdi S.
    Plataniotis, Konstantinos N.
    [J]. 2018 25TH IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP), 2018, : 296 - 300
  • [8] Image Sharpness Metric Based on Algebraic MultiGrid Method
    Ying, Qian
    Xue-Mei, Ren
    Ying, Huang
    Li, Meng
    [J]. INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS, 2014, 5 (04) : 175 - 179
  • [9] No-reference retinal image sharpness metric using daubechies wavelet transform
    Vonghirandecha, P.
    Bhurayanontachai, P.
    Kansomkeat, S.
    Intajag, S.
    [J]. International Journal of Circuits, Systems and Signal Processing, 2021, 15 : 1064 - 1071
  • [10] No-reference Image Sharpness Metric Based on Directional Derivatives
    Qian, Jiye
    Zhao, Hengjun
    Fu, Jin
    He, Guojun
    Hou, Xingzhe
    Fang, Bin
    Qian, Jide
    [J]. 2017 INTERNATIONAL CONFERENCE ON SECURITY, PATTERN ANALYSIS, AND CYBERNETICS (SPAC), 2017, : 340 - 344