Image processing uses many data processing techniques to transform the raw data or information from a sensor system into useful information from which decisions can be made. Historically, the data processing systems associated with each image processing application were tuned or optimized to that application such as machine inspection, pattern recognition, etc. In today's environment it is desi...

Due to increased use of imaging sensors in military aircraft, future combat airplane pilots will need onboard artificial intelligence for aiding them in image interpretation and target designation. This document presents a system which is able to create high-resolution artificial SAR imagery. The resulting images can be used to facilitate automatic target recognition (ATR) algorithm development...

Target detection is one of the important elements of Automatic Target Recognition (ATR) systems. In this paper, we propose a new approach to detect outliers in radar returns, based on modelling the background using an empirical distribution rather than a parametric distribution. The key innovation lies in the use of the Characteristic Function (CF) to describe the distribution. The experimental...

Recent developments in target decomposition theorems indicates that the polarimetric signature of a target describes scattering mechanisms, such as depolarization, even bounce, or odd bounce, that may assist in the differentiation of a man-made targets from natural clutter, a critical first step in Automatic Target Recognition (ATR). Cloude’s alpha-entropy decomposition of the coherency matrix,...

This paper describes and evaluates the types of machine learning techniques which are appropriate for the special needs of automatic target recognition. Artiicial neural networks has been the most popular choice. However, they have several shortcomings , including that they do not readily allow the learned domain theory to be revised in response to new conditions, new targets, or new sensors. R...

In recent years, statistical approaches on ATR (Automatic Term Recognition) have achieved good results. However, there are scopes to improve the performance in extracting terms still further. For example, domain dictionaries can improve the performance in ATR. This paper focuses on a method for extracting terms using a dictionary hierarchy. Our method produces relatively good results for this t...

Most Automatic Target Recognition (ATR) algorithms operate in 2D image space. Even when using 3D models, these 3D models are typically translated o -line into sets of 2D representations, such as templates, which are then applied to imagery to perform detection, recognition and veri cation. In contrast to this approach, the work reported here takes steps toward direct matching of 3D models to ra...

Target detection is the front-end stage in any automatic target recognition system for synthetic aperture radar (SAR) imagery (SAR-ATR). The efficacy of the detector directly impacts the succeeding stages in the SAR-ATR processing chain. There are numerous methods reported in the literature for implementing the detector. We offer an umbrella under which the various research activities in the fi...

An ATR algorithm for low quality imagery is reported. Compact shaped targets are represented by their 2D silhouettes. Associated with each point on the silhouette, there is a direction roughly perpendicular to the local segment of the silhouette. The location of each silhouette point is assumed to be perturbed along that direction. A statistical technique is used to estimate the variance of tha...