Superresolution for translated satellite images using the Walsh functions

Naceur Omrane; Phil L. Palmer

doi:10.1117/12.511478

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5 February 2004 Superresolution for translated satellite images using the Walsh functions

Naceur Omrane, Phil L. Palmer

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Proceedings Volume 5238, Image and Signal Processing for Remote Sensing IX; (2004) https://doi.org/10.1117/12.511478
Event: Remote Sensing, 2003, Barcelona, Spain

Abstract

The aim of Super-Resolution techniques is to produce a high-resolution image from a sequence of shifted low-resolution images. These low-resolution images are generally taken from slightly different viewpoints, which can result in some new information from one image to another. Super-resolution is a very attractive research area and finds its applications in many domains. We present in this paper a new algorithm to achieve image Super-Resolution suitable for sequences of satellite images. The shift between images is estimated using a new measure based upon the sharpness property of edges in the reconstructed image. The reconstruction is performed using a new approach to super-resolution based on the orthogonal set of Walsh-functions. In this paper we shall derive an expression for the missing information contained in an image of 2^M+1 pixels but absent in the lower resolution image of 2^M pixels. From this we prove how this information can be retrieved from a second image containing 2^M pixels, shifted from the first by an arbitrary amount. We then derive analytic models for the distortion of edge information by this process and use the blurring in the reconstructed image to perform accurate registration between the two shifted images at low resolution. We present results from this method based upon test imagery where the shift is known a priori to evaluate performance.

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Naceur Omrane and Phil L. Palmer "Superresolution for translated satellite images using the Walsh functions", Proc. SPIE 5238, Image and Signal Processing for Remote Sensing IX, (5 February 2004); https://doi.org/10.1117/12.511478

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