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      Deep Learning in Remote Sensing: A Comprehensive Review and List of Resources

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          Extreme learning machine: Theory and applications

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            Video Google: a text retrieval approach to object matching in videos

             Sivic,  Zisserman (2003)
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              Stereo processing by semiglobal matching and mutual information.

              This paper describes the Semi-Global Matching (SGM) stereo method. It uses a pixelwise, Mutual Information based matching cost for compensating radiometric differences of input images. Pixelwise matching is supported by a smoothness constraint that is usually expressed as a global cost function. SGM performs a fast approximation by pathwise optimizations from all directions. The discussion also addresses occlusion detection, subpixel refinement and multi-baseline matching. Additionally, postprocessing steps for removing outliers, recovering from specific problems of structured environments and the interpolation of gaps are presented. Finally, strategies for processing almost arbitrarily large images and fusion of disparity images using orthographic projection are proposed.A comparison on standard stereo images shows that SGM is among the currently top-ranked algorithms and is best, if subpixel accuracy is considered. The complexity is linear to the number of pixels and disparity range, which results in a runtime of just 1-2s on typical test images. An in depth evaluation of the Mutual Information based matching cost demonstrates a tolerance against a wide range of radiometric transformations. Finally, examples of reconstructions from huge aerial frame and pushbroom images demonstrate that the presented ideas are working well on practical problems.
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                Author and article information

                Journal
                IEEE Geoscience and Remote Sensing Magazine
                IEEE Geosci. Remote Sens. Mag.
                Institute of Electrical and Electronics Engineers (IEEE)
                2168-6831
                2473-2397
                December 2017
                December 2017
                : 5
                : 4
                : 8-36
                Article
                10.1109/MGRS.2017.2762307
                © 2017
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