Pyramidal Image Processing Using Morphology

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Abstract
Linear pyramidal image processing (LPIP) is a form of multiresolution analysis in which a primary image is decomposed into a set of different resolution copies. LPIP aims to extract and interpret significant features of an image appearing at different resolutions. Morphological filtering, a nonlinear image processing technique, because of its simplicity of operation and its direct relation to the shapes in an image, has been widely studied. In this paper, the use of morphological filtering technique for a nonlinear pyramidal image processing (NPIP) is proposed. By using a set of desirably structured masks as the 'Structuring Elements" (SEs), a primary image is decomposed into a sequence of pyramidal image copies. For each Gaussian image pyramid, objects smaller than a predetermined image threshold size are filtered, while for each Laplacian pyramid, objects other than a predetermined size are blocked. For NPIP operation, pipelined and parallel software implementation algorithms are suggested. In order to reconstruct the original image, an inverse morphologic transform with some special Structuring Elements is considered.

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