Noisy Synthetic Aperture Radar Image Research Articles

Watershed identification of polygonal patterns in noisy SAR images

This paper describes a new approach to pattern recognition in synthetic aperture radar (SAR) images. A visual analysis of the images provided by NASA's Magellan mission to Venus has revealed a number of zones showing polygonal-shaped faults on the surface of the planet. The goal of the paper is to provide a method to automate the identification of such zones. The high level of noise in SAR images and its multiplicative nature make automated image analysis difficult and conventional edge detectors, like those based on gradient images, inefficient. We present a scheme based on an improved watershed algorithm and a two-scale analysis. The method extracts potential edges in the SAR image, analyzes the patterns obtained, and decides whether or not the image contains a "polygon area". This scheme can also be applied to other SAR or visual images, for instance in observation of Mars and Jupiter's satellite Europa.

Classification of pixels in a noisy grayscale image of polar ice

Often, in synthetic aperture radar (SAR) images of polar ice, one encounters shadow-like features across the images. Such features make it difficult to classify pixels into ice and water. Accordingly, it becomes a challenge to determine the true size and boundaries of ice floes in an SAR image of polar ice. We develop a simple statistical procedure which classifies pixels of an image by eliminating the effects of shadow-like features. Methodology developed in this paper is illustrated using some noisy SAR images of ice floes in the Arctic sea.

The Radon transform on a dynamically switched transputer network

Previously reported work resulted in a transputer tree network using thirty tramputers to perform the Radon transform. The Radon transform was used to enhance linear features in noisy synthetic aperture radar images. The work presented here describes modification of the transputer network by the addition of INMOS B004 link switches, and controlling T222 transputer. The tree configuration is replaced such that link switches now dynamically switch between the image data source transputer (farmer) and the transputers which perform the calculations (workers). It is shown that this arrangement is more cost-effective since the worker transputers are all relieved of their data-routing role. The paper Includes a comparison of the previous tree network with the new switched network, and presents results for both techniques.