Abstract
Strip noise is one of the important factors affecting the quality of the imaginary acquired from space and the further processing on information retrieving from MODIS 1B image.Aiming at the characteristics of strip noise in Band 5 of MODIS 1B image,the cause of strip noise formation was described,and the commonly used methodologies and principles for destriping imaginaries from several different sensors were systematically compared with discussions focusing mainly on their constraints in operations.In this study,the Fourier Transform Algorithm,the most frequently used methodology for destriping,was experimentally utilized for strip noise removal in MODIS 1B image,and in the light of self-correlation characteristic of MODIS data,a new approach by means of self-correlation interpolation algorithm for effective removal of strip noise in Band 5 of MODIS image was proposed.Comparison of mean values and standard deviations as well as edge affection obtained from the strip noise removed image by these two methodologies suggested that self-correlation interpolation algorithm is evidently superior to the traditional Fourier transform algorithm in destriping MODIS 1B products.
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