A random-field model-based algorithm for anomalous complex image pixel detection

被引:3
作者
Bello, Martin G. [1 ]
机构
[1] Charles Stark Draper Lab Inc, Cambridge, MA 02139 USA
关键词
D O I
10.1109/83.136595
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Random-field model-based algorithms for the detection of anomalous pixels associated with complex valued imagery may be essential to robust focus of attention, target detection, and cuing. The described algorithm includes the fitting of a specific class of causal, two-dimensional autoregressive random-field models to image data over specified estimation windows, and then subsequent construction of prediction error samples over specified detection windows. Statistical testing of the calculated prediction error samples is then used to localize anomalous image pixels. Experimental results obtained from running the described algorithm on SAR imagery are included.
引用
收藏
页码:186 / 196
页数:11
相关论文
共 24 条
  • [1] STATISTICAL PREDICTOR IDENTIFICATION
    AKAIKE, H
    [J]. ANNALS OF THE INSTITUTE OF STATISTICAL MATHEMATICS, 1970, 22 (02) : 203 - &
  • [2] BELLO MG, 1987, EM2651 AN SCI CORP
  • [3] Belsley D. A., 2005, REGRESSION DIAGNOSTI
  • [4] Chow Y., 1978, PROBABILITY THEORY I
  • [5] Dudgeon D. E., 1984, MULTIDIMENSIONAL DIG
  • [6] 2-DIMENSIONAL SPECTRAL FACTORIZATION WITH APPLICATIONS IN RECURSIVE DIGITAL FILTERING
    EKSTROM, MP
    WOODS, JW
    [J]. IEEE TRANSACTIONS ON ACOUSTICS SPEECH AND SIGNAL PROCESSING, 1976, 24 (02): : 115 - 128
  • [7] Golub G.H., 1983, MATRIX COMPUTATIONS
  • [8] GRENADER U, 1984, STAT ANAL STAT TIMES
  • [9] Hampel FR., 1986, ROBUST STAT APPROACH
  • [10] HANSEN RR, 1988, IEEE T ACOUST SPEECH, V36