An Inquiry on Contrast Enhancement Methods for Satellite Images

Abstract

Enhancement algorithms are absolutely necessary for the visualization of both shadowed and bright image regions. Defining algorithms that permit to visualize them simultaneously without altering the image content is therefore extremely relevant for remote sensing applications. In this paper, we present the results of two successive benchmarks which tested the performance of the state-of-the-art contrast enhancement and tone-mapping algorithms applied to satellite images. Experts from the French Space Agency Centre National d'Etudes Spatiales (CNES), Service Regional de Traitement d'Image et de Teledetection (SERTIT), and two European universities assessed the quality and fidelity of the results of several state-of-the-art enhancement algorithms on the excerpts from seven images (five Pleiades and two simulated 30-cm images). The first benchmark permitted to tighten the procedure and the selection of the test images for the second one, and to make a first selection of concurrent algorithms. The second benchmark not only included the best algorithms selected by the first benchmark but also added even more competitors in the tone-mapping class. The results of both benchmarks were coherent. They point a particular retinex-based algorithm as the best compromise between the competitive requirements of a contrast enhancement in dark regions and a preservation of detail in bright parts.