Segmenting a document image into text and picture areas is very important for compressing efficiently document images. This paper introduces an algorithm of multiscale image segmentation for document image compression...Segmenting a document image into text and picture areas is very important for compressing efficiently document images. This paper introduces an algorithm of multiscale image segmentation for document image compression,which uses of wavelet-domain hidden Markov tree model in order to directly calculate the parameter of model based on original image to be segmented,and to obtain multiscale classification and segmentation of image. The idea of the method is to combine several new technologies such as multilevel wavelet transform,multiscale decision,across-scale dependencies and joint probability density function. The paper describes in detail the concept of the dyadic block,the correspondency between wavelets and dyadic blocks based on quad-tree,the hidden Markov model and multiscale likelihood computation.展开更多
文摘Segmenting a document image into text and picture areas is very important for compressing efficiently document images. This paper introduces an algorithm of multiscale image segmentation for document image compression,which uses of wavelet-domain hidden Markov tree model in order to directly calculate the parameter of model based on original image to be segmented,and to obtain multiscale classification and segmentation of image. The idea of the method is to combine several new technologies such as multilevel wavelet transform,multiscale decision,across-scale dependencies and joint probability density function. The paper describes in detail the concept of the dyadic block,the correspondency between wavelets and dyadic blocks based on quad-tree,the hidden Markov model and multiscale likelihood computation.
