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Proceedings Paper

Resolution enhancement of tri-stereo remote sensing images by super resolution methods
Author(s): Caglayan Tuna; Alper Akoguz; Gozde Unal; Elif Sertel
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Paper Abstract

Super resolution (SR) refers to generation of a High Resolution (HR) image from a decimated, blurred, low-resolution (LR) image set, which can be either a single frame or multi-frame that contains a collection of several images acquired from slightly different views of the same observation area. In this study, we propose a novel application of tri-stereo Remote Sensing (RS) satellite images to the super resolution problem. Since the tri-stereo RS images of the same observation area are acquired from three different viewing angles along the flight path of the satellite, these RS images are properly suited to a SR application. We first estimate registration between the chosen reference LR image and other LR images to calculate the sub pixel shifts among the LR images. Then, the warping, blurring and down sampling matrix operators are created as sparse matrices to avoid high memory and computational requirements, which would otherwise make the RS-SR solution impractical. Finally, the overall system matrix, which is constructed based on the obtained operator matrices is used to obtain the estimate HR image in one step in each iteration of the SR algorithm. Both the Laplacian and total variation regularizers are incorporated separately into our algorithm and the results are presented to demonstrate an improved quantitative performance against the standard interpolation method as well as improved qualitative results due expert evaluations.

Paper Details

Date Published: 18 October 2016
PDF: 8 pages
Proc. SPIE 10004, Image and Signal Processing for Remote Sensing XXII, 1000409 (18 October 2016); doi: 10.1117/12.2241176
Show Author Affiliations
Caglayan Tuna, Istanbul Technical Univ. (Turkey)
Alper Akoguz, Istanbul Technical Univ. (Turkey)
Gozde Unal, Istanbul Technical Univ. (Turkey)
Elif Sertel, Istanbul Technical Univ. (Turkey)


Published in SPIE Proceedings Vol. 10004:
Image and Signal Processing for Remote Sensing XXII
Lorenzo Bruzzone; Francesca Bovolo, Editor(s)

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