| Summary: | This paper focuses on how a method for automated programming (i.e., genetic programming) applies in the computeraided discovery of algorithms that enhance and extract features from remotely sensed images. Highlighted as a case study is the use of this method in the problem of extracting pressure ridge features from ERS-1 SAR imagery; a problem for which there has been no known satisfactory solution. 1. INTRODUCTION Pressure ridges in arctic ice are a significant geophysical feature in sea-ice research. [1] Pressure ridges (and their corresponding keels, which are below-water features) help to transfer kinetic energy from meteorological systems and polar oceanic currents to the ice pack. In particular, pressure ridges and keels significantly increase sea-ice drag coefficients, which subsequently affect sea-ice movement and deformation. To observe meso-scale features such as pressure ridges, researchers have used satellite SAR (synthetic aperture radar) imagery. In such imagery, press.
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