The Application of the Model of High-Speed Pixel Clustering in Problems of Preprocessing of the Images of the Remote Sensing of the Earth

Abstract

The purpose of the research is to use the modified Ward’s method in high-speed processing of full-HD images of the remote sensing of the Earth. The classical Ward’s method is modified by dividing the computational process into three successive stages. The first stage quickly builds a coarse hierarchy of approximations. The second stage performs a quality improvement of the specified partition for a fixed number of colors (clusters). The third stage is the clustering of the superpixels using the Ward’s method. The software-algorithmic toolkit consists of four operations on clusters of pixels and image segments: merge operation joins together two clusters; divide operation reversibly disjoins the selected cluster into two; split operation extracts the part of the cluster into individual cluster; correct operation reclassifies pixels by extracting from one cluster and inserting into another cluster. The quality is assessed by the total squared error. The quality improvement is provided by iterative execution of a combination of merge and divide operations of pixel clusters, in particular image segments. One of the clusters (segments) is divided in two and a pair of other mismatched with it is combined into one according to the criterion of the minimum increment of the total squared error. The proposed modified Ward’s method is appropriate in processing of fullHD images of the remote sensing of the Earth. The results of processing in pure segmentation and clustering modes are compared. The proposed pixel clustering model is appropriate in high-speed processing of the fullHD images. The pixel clustering in comparison with image segmentation allows to define in more detail both the contours of objects of interest and their internal structure