Hierarchical and multiscale Mean Shift segmentation of population grids
نویسندگان
چکیده
The Mean Shift (MS) algorithm allows to identify clusters that are catchment areas of modes of a probability density function (pdf). We propose to use a multiscale and hierarchical implementation of the algorithm to process grid data of population and identify automatically urban centers and their dependant sub-centers through scales. The multiscale structure is obtained by increasing iteratively the bandwidth of the kernel used to define the pdf on which the MS algorithm works. This will induce a hierarchical structure over clusters since modes will merge together when the bandwidth parameter increases.
منابع مشابه
Unsupervised Multiscale Image Segmentation
We propose a general unsupervised multiscale featurebased approach towards image segmentation. Clusters in the feature space are assumed to be properties of underlying classes, the recovery of which is achieved by the use of the mean shift procedure, a robust non-parametric decomposition method. The subsequent classification procedure consists of Bayesian multiscale processing which models the ...
متن کاملHierarchical Layered Mean Shift Methods
Many image processing tasks exist and segmentation is one of them. We are focused on the mean-shift segmentation method. Our goal is to improve its speed and reduce the over-segmentation problem that occurs with small spatial bandwidths. We propose new mean-shift method called Hierarchical Layered Mean Shift. It uses hierarchical preprocessing stage and stacking hierarchical segmentation output...
متن کاملSpatio-temporal Segmentation of Video by Hierarchical Mean Shift Analysis
We describe a simple new technique for spatio-temporal segmentation of video sequences. Each pixel of a 3D space-time video stack is mapped to a 7D feature point whose coordinates include three color components, two motion angle components and two motion position components. The clustering of these feature points provides color segmentation and motion segmentation, as well as a consistent label...
متن کاملA Hierarchical, Multiscale Texture Segmentation Algorithm for Real-World Scenes
1. Texture segmentation can lead to multiscale outputs in which the partitions at successive scales are nested. 2. We can incorporate hierarchical segmentation into a K-Means clustering technique by steadily relaxing inter-cluster distances. 3. Thus, it is possible to hierarchically segment images based solely on texture measurements. 4. This hierarchical, multiscale segmentation is useful in i...
متن کاملA New Color Image Segmentation Algorithm Combining Mean Shift and Hierarchical Clustering ?
A new color image segmentation method combining mean shift and hierarchical clustering algorithm is presented in this paper. The proposed algorithm preprocesses an input image by mean shift algorithm to form segmented regions that preserve the desirable discontinuity characteristics of image. The number of segmented regions, instead of the number of image pixels, is considered as the input data...
متن کامل