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de Souza Filho, C. R.; Drury, S. A.; Denniss, A. M.; Carlton, R. W. T. and Rothery, D. A.
(1996).
URL: http://www.asprs.org/a/publications/pers/96journal...
Abstract
The image data collected by Fuyo-1's sensors covering the visible and the short wave infrared (SWIR) are affected by severe noise problems. The important narrow SWIR channels show the worst defects. Artifacts originally introduced by the satellite sensors (unprocessed Level 0 data) were exaggerated by the Earth-rotation correction applied by NASDA (Level 2 data). Fourier analysis is used to characterize these artifacts in the frequency domain. A scene-dependent Fourier operator that is able to eliminate the major noise components is described. This involves the construction of a binary mask derived from the difference between the Fourier spectra of two channels containing noise signals at similar frequencies and amplitude. This mask is used to modulate frequency domain images, so removing all noise components while preserving real image data with minimum loss and distortion in the spatial domain. Fuyo-1 brightness saturation problems can also be minimized by applying a Gaussian contrast stretch to the Fourier spectra prior to image inversion. Based on our initial results using the recovery methods proposed here, we foresee an exciting new use for the thousands of seven-channel images already acquired by Fuyo-1.