Abstract
This paper presents a methodology for high resolution image classification and segmentation. The size and information volume of the images, taken by a high resolution digital camera, will be tens to hundreds times as the ones taken by an ordinary CCD camera. In order to speed up the image segmentation process of the large images, we classify the images first by using a low resolution image, then, segment them by a fast segmentation algorithm. The algorithm is studied mainly based on multi-resolution technique and the fusion of edge detection result and similarity segmentation result. By using this methodology, the whole image segmentation process time is reduced by tens' times than traditional segmentation methods, and the accuracy of the image segmentation is not decreased.
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