In this paper, the problem of segmentation of smooth images has been studied using multiresolution analysis. The approximated image intensity function is modeled as a quadratic polynomial with additive noise within local windows. The analysis has been carried out with the aid of a new orthonormal wavelet basis introduced in this paper. A procedure has been developed to approximate an image at a coarse resolution by dropping the components of the image in such a way that small bumps at finer resolutions are suppressed. An image segmentation scheme is proposed. It performs initial segmentation on a coarse approximation of the image, and then updates the segments of the image at a finer resolution. The proposed algorithm has been tested on a variety of real images such as human faces, natural scenes, and medical images.
Smooth image segmentation via multiresolution analysis
Wavelet Applications in Signal and Image Processing II ; 1994 ; San Diego,CA,United States
Proc. SPIE ; 2303
1994-10-11
Conference paper
Electronic Resource
English
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