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Proceedings Paper

Assessing the spatial fidelity of resolution-enhanced imagery using Fourier analysis: a proof-of-concept study
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Paper Abstract

Pan-sharpening of moderate resolution multispectral remote sensing data with those of a higher spatial resolution is a standard practice in remote sensing image processing. This paper suggests a method by which the spatial properties of resolution merge products can be assessed. Whereas there are several accepted metrics, such as correlation and root mean square error, for quantifying the spectral integrity of fused images, relative to the original multispectral data, there is less agreement on a means by which to assess the spatial properties, relative to the original higher-resolution, pansharpening data. In addition to qualitative, visual, and somewhat subjective evaluation, quantitative measures used have included correlations between high-pass filtered panchromatic and fused images, gradient analysis, wavelet analysis, among others. None of these methods, however, fully exploits the spatial and structural information contained in the original high resolution and fused images. This paper proposes the use of the Fourier transform as a means to quantify the degree to which a fused image preserves the spatial properties of the pan-sharpening high resolution data. A highresolution 8-bit panchromatic image was altered to produce a set of nine different test images, as well as a random image. The Fourier Magnitude (FM) image was calculated for each of the datasets and compared via FM to FM image correlation. Furthermore, the following edge detection algorithms were applied to the original and altered images: (a) Canny; (b) Sobel; and (c) Laplacian. These edge-filtered images were compared, again by way of correlation, with the original edge-filtered panchromatic image. Results indicate that the proposed method of using FTMI as a means of assessing the spatial fidelity of high-resolution imagery used in the data fusion process outperforms the correlations produced by way of comparing edge-enhanced images.

Paper Details

Date Published: 25 October 2012
PDF: 13 pages
Proc. SPIE 8538, Earth Resources and Environmental Remote Sensing/GIS Applications III, 853805 (25 October 2012); doi: 10.1117/12.974703
Show Author Affiliations
Daniel L. Civco, Univ. of Connecticut (United States)
Chandi Witharana, Univ. of Connecticut (United States)

Published in SPIE Proceedings Vol. 8538:
Earth Resources and Environmental Remote Sensing/GIS Applications III
Shahid Habib; Ulrich Michel; Daniel L. Civco; David Messinger; Antonino Maltese; Manfred Ehlers; Karsten Schulz; Konstantinos G. Nikolakopoulos, Editor(s)

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