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We demonstrate an automated stereo-matching algorithm capable of extracting disparity/depth information from stereo image pairs with an unconventionally narrow baseline separation i.e. low base-to-height ratio (B/H), thus potentially allowing digital elevation models (DEMs) to be derived from images that previously might not have been considered suitable for stereo applications. For very small B/H ratios the disparity magnitudes may be reduced to sub-pixel levels that conventional stereo-matching algorithms fail to measure. By utilising a new sub-pixel image matching algorithm, based upon the phase correlation (PC) method, we are able to measure the very subtle, sub-pixel, disparities that result from image pairs with B/H ratios as small as 0.06. Initial tests with this algorithm on SPOT 5 satellite image data have demonstrated that this routine is capable of generating very dense and detailed disparity/depth maps of a scene for DEM generation without prior knowledge of the satellite/sensor parameters, whilst also being exceptionally sensitive to small scale textural features, robust to noise, and efficient to implement.