MOS-B data corrected by standard calibration procedures are affected by 'striping' in most channels. Striping arises because of the imperfect calibration of the detector characteristics. In this paper, we present a method for removing striping, in which the equalization curves are estimated by exploiting a data base of carefully selected homogeneous targets. We present the results obtained on sea target images. Such a case study is of great interest because it is related to ocean color applications, for which the MOS-B sensor was especially designed. We also estimate the reduction of striping noise in the equalized image by means of two appropriate indexes of quality
In the Institute for Space Sensor Technology a new generation of remote sensing imaging spectrometers was developed, measuring the reflected from the ocean atmosphere system radiance in the visible to near-infrared spectral range. This Modular Optical Scanner (MOS) was successfully launched on 21 March 1996 with an Indian satellite (IRS-P3) to a polar sunsynchronous orbit, and on 23 April 1996 with the Russian Priroda Module on the MIR station. For the purpose of interpretation of these measurements over oceans and coastal zones has been developed a special algorithm based on Principal Component Analysis, using a special inversion technique fx a given ocean-atmosphere physical model. An important question in the description of such models are the inherent optical properties of the water. In the paper will be given a description of the derivation of the interpretation algorithm f different water constituents, with an inherent atmospheric correction. It will be shown how specific optical properties are influencing the interpretation results. This work was peilormed in cooperation with the Baltic Sea Research Institute Warnemuende. /97/$1O.OO Downloaded From: http://proceedings.spiedigitallibrary.org/ on 05/28/2015 Terms of Use: http://spiedl.org/terms 7. Prieur L, Sathyendranath S.: Limnol. and Oceanogr. 26(1981)4, pp. 671ff. 8. Neumann A. et: al.: A complex approach to quantitative Interpretation of spectral high resolution imagery,
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