Processes for conducting HSI and MSI pan-sharpening with 3D digital flattening

Tyler R. Peery; David Messinger

doi:10.1117/12.2304375

8 May 2018 Processes for conducting HSI and MSI pan-sharpening with 3D digital flattening

Tyler R. Peery, David Messinger

Proceedings Volume 10644, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XXIV; 106441W (2018) https://doi.org/10.1117/12.2304375
Event: SPIE Defense + Security, 2018, Orlando, FL, United States

Abstract

Two-dimensional digital flattening was implemented on distorted 3D documents for the Rochester Cultural Heritage Imaging, Visualization, and Education (R-CHIVE) database, with the purpose of exploring new techniques to enhance usability among historians and analysts. This process was investigated with a minimal cost RGB scanner for implementation into a future hyperspectral system. Results from the flattening improved readability of the distorted document when compared to a simple nadir view. The flattening process was then combined with pan-chromatic sharpening to produce a high spatial and spectral resolution image removed of projective distortion. The effectiveness of processing order was investigated relative to spectral, spatial, and flattening accuracy. Flattening and then sharpening proved more accurate both spectrally and spatially, with 60% the spectral error and 80% less FWHM of its line spread function. Two flattening methods were investigated and again the flattening first method outperformed the sharpening then flattening method, this time by 38.7%. This suggests, for simple flattening requirements, sharpening the image first, applying it to the 3D model, and then flattening the model provides the most accurate results.

Citation Download Citation

Tyler R. Peery and David Messinger "Processes for conducting HSI and MSI pan-sharpening with 3D digital flattening", Proc. SPIE 10644, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XXIV, 106441W (8 May 2018); https://doi.org/10.1117/12.2304375

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KEYWORDS

Multispectral imaging

Image processing

Cameras

Sensors

3D image processing

3D modeling

Distortion

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