Vectorization Method on the Color Cloud Image

Abstract

The vectorization, which is an interdisciplinary combining subjects of the computer vision, computer image processing, computer graphics and artificial intelligence, is an important issue in the digital image processing. This paper makes a study of the vectorization method on the satellite color cloud image, Specific techniques such as cloud image layering, threshold selection, edge detection and tracking, feature point extraction, curve fitting are involved. This paper proposes a color layering algorithm whose parameter is the difference between luminance and saturability by analyzing the color features of the satellite cloud pictures. In this algorithm method, we first generate the reference image and then histogram equalize the reference image, afterwards do de-noises process to the above histogram and smooth it for the threshold choice. After analyzing the uncertainty of satellite cloud image edge, this paper puts forward an edge detection algorithm based on adaptive threshold. In order to modify the shortcomings of edge data of raster and edge data of chain code, this paper puts forward the corner detection method based on edge data chain. Also this paper develops a prototype system of automatic vectorization on satellite cloud images by curve fitting the feature points and gets the final vector graphics. Experiments show that the system has the basic functions of automatic extraction, recognition and vectorization for the information of satellite cloud clouds, and carry out the comprehensive verification and analysis for the theory and algorithm by using the real satellite cloud image data.