18 January 2010 Remote sensing image enhancement integrating its local statistical characteristics
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Abstract
Remote sensing is widely used to assess the destruction from natural disasters and to plan relief and recovery operations. How to automatically extract useful features and segment interesting objects from digital images, including remote sensing imagery, becomes a critical task for image understanding. Unfortunately, the data collection of aerial digital images is constrained with bad weather, muzzy atmosphere, and unstable camera or camcorder. As a result, remote sensing imagery is shown as lowcontrast, blurred, and dark from time to time. Here, we introduce a new method integrating image local statistics and image natural characteristics to enhance remote sensing imagery. This method computes the adaptive histogram equalization to each distinct region of the input image and then redistributes the lightness values of the image. The natural characteristic of image is applied to adjust the restoration contrast. The experiments on real data show the effectiveness of the algorithm.
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Qiang He, Qiang He, Chee-Hung Henry Chu, Chee-Hung Henry Chu, "Remote sensing image enhancement integrating its local statistical characteristics", Proc. SPIE 7529, Image Quality and System Performance VII, 75290O (18 January 2010); doi: 10.1117/12.838472; https://doi.org/10.1117/12.838472
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