The implementation of a non-iterative atmospheric correction algorithm is described in detail and the performance of the algorithm is illustrated for several CZCS images. Chlorophyll retrieval is attempted using linear, power and polynomial regression for ratios of corrected images and the best correlation coefficients are in the region of 0-9. The same images are analysed in three spectral bands using the ISOCLS clustering algorithm and ocean areas are stratified into subclass patterns which correlate well with ratios and sea-truth. The monocluster blocks approach is used to extract training statistics for maximum likelihood classification of ocean areas and the results compare favourably with corresponding ratio images.