Title :
A random-field model-based algorithm for anomalous complex image pixel detection
Author :
Bello, Martin G.
Author_Institution :
Charles Stark Draper Lab., Cambridge, MA, USA
fDate :
4/1/1992 12:00:00 AM
Abstract :
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 curing. 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 (synthetic aperture radar) imagery are included
Keywords :
picture processing; signal detection; 2D AR models; SAR imagery; anomalous complex image pixel detection; causal models; curing; detection windows; estimation windows; image data; prediction error samples; random field model algorithm; synthetic aperture radar; target detection; Computer vision; Cultural differences; Focusing; Helium; Object detection; Object recognition; Pixel; Predictive models; Robustness; Statistical analysis;
Journal_Title :
Image Processing, IEEE Transactions on
