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In this paper a new method of image smoothing for satellite imagery and itsapplications in environmental remote sensing are presented. This method isbased on the global gradient minimization over the whole image. With respect tothe image discrete identity, the continuous minimization problem isdiscretized. Using the finite difference numerical method of differentiation, asimple yet efficient 5*5-pixel template is derived. Convolution of the derivedtemplate with the image in different bands results in the discrimination ofvarious image elements. This method is extremely fast, besides being highlyprecise. A case study is presented for the northern Iran, covering parts of theCaspian Sea. Comparison of the method with the usual Laplacian template revealsthat it is more capable of distinguishing phenomena in the image.

Identification and Classification of Phenomena in Multispectral  Satellite Imagery Using a New Image Smoother Method and its Applications in  Environmental Remote Sensing