SPIE - Education Sensor Arrays for Source Detection and Identification in Image Analysis SC1190

A sensor array outperforms a single sensor in source detection and identification for the purposes of accuracy, precision, resolution, and efficiency. Examples of sensor arrays include the Very Large Baseline Array (VLBA), Phase Array Radar (PAR), and Synthetic Aperture Radar (SAR). An image of a scene generated by various sensor arrays is a visual representation of the mixture of signals from sources in the scene. By sampling the image into sub-images, source detection and identification in image analysis is translated into a sensor array signal processing framework, where distinctive object regions in the image and the sampled sub-images serve as sources and sensors. Further sampling of the sub-images and averaging pixel data yield observations for the sensors, and an analysis of the resulting covariance matrix provides information on the number of sources and source identification. . The theoretical and experimental results obtained by applying this approach on images generated by various sensor array systems are shown to be in good agreement. The similarities and differences between this approach and (1) Independent Component Analysis (ICA), (2) Time Series Autoregressive (AR) model, (3) Multispectral image analysis, and (4) Multivariate image analysis are described.