Abstract
An image processing methodology is presented to recover the quality of the Multifunctional Transport Satellite (MTSAT)-1R visible channel data affected by spatial crosstalk. The slight blurring of the visible optical path is attributed to an imperfection in the mirror surface caused either by flawed polishing or a dust contaminant. The methodology assumes that the dispersed portion of the signal is small and distributed randomly around the optical axis, which allows the image to be deconvolved using an inverted point spread function (PSF). The PSF is described by four parameters, which are solved using a maximum-likelihood estimator using coincident collocated MTSAT-2 images as truth. A subpixel image matching technique is used to align the MTSAT-2 pixels into the MTSAT-1R projection and to correct for navigation errors and cloud displacement due to the time and viewing geometry differences between the two satellite observations. An optimal set of the PSF parameters is derived by an iterative routine based on the 4-D Powell's conjugate direction method that minimizes the difference between the PSF-corrected MTSAT-1R and the collocated MTSAT-2 images. The PSF parameters were found to be consistent over the 5 days of available daytime coincident and MTSAT-1R and MTSAT-2 images. After applying the PSF parameters, the visible sensor response is nearly linear, and the space count is close to zero. The overall linear regression standard error was reduced by 52%. Users can easily apply the PSF parameter coefficients to the MTSAT-1R imager pixel level counts to restore the original quality of the entire MTSAT-1R record.
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