Automated image processing and fusion for remote sensing applications

Sakina Zabuawala; Hai Wei; Chaitanya Raju; Nilanjan Ray; Jacob Yadegar

doi:10.1117/12.806081

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2 February 2009 Automated image processing and fusion for remote sensing applications

Sakina Zabuawala, Hai Wei, Chaitanya Raju, Nilanjan Ray, Jacob Yadegar

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Proceedings Volume 7246, Computational Imaging VII; 724612 (2009) https://doi.org/10.1117/12.806081
Event: IS&T/SPIE Electronic Imaging, 2009, San Jose, California, United States

Abstract

The ever increasing volumes and resolutions of remote sensing imagery have not only boosted the value of image-based analysis and visualization in scientific research and commercial sectors, but also introduced new challenges. Specifically, processing large volumes of newly acquired high-resolution imagery as well as fusing them against existing imagery (for correction, update, and visualization) still remain highly subjective and labor-intensive tasks, which has not been fully automated by the existing GIS software tools. This calls for the development of novel computational algorithms to automate the routine image processing tasks involved in various remote sensing based applications. In this paper, a suite of efficient and automated computational algorithms has been proposed and developed to address the aforementioned challenge. It includes a segmentation algorithm to achieve the automatic "cleaning" (i.e. segmenting out the valid pixels) of any newly acquired ortho-photo image, automatic feature point extraction, image alignment by maximization of mutual information and finally smoothing/feathering the edges of the imagery at the join zone. The proposed algorithms have been implemented and tested using practical large-scale GIS imagery/data. The experimental results demonstrate the efficiency and effectiveness of the proposed algorithms and the corresponding capability of fully automated segmentation, registration and fusion, which allows the end-user to bring together image of heterogeneous resolution, projection, datum, and sources for analysis and visualization. The potential benefits of the proposed algorithms include great reduction of the production time, more accurate and reliable results, and user consistency within and across organizations.

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Sakina Zabuawala, Hai Wei, Chaitanya Raju, Nilanjan Ray, and Jacob Yadegar "Automated image processing and fusion for remote sensing applications", Proc. SPIE 7246, Computational Imaging VII, 724612 (2 February 2009); https://doi.org/10.1117/12.806081

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