영상내의 잡음특성에 따른 적응적 쿼드트리 영상분할방법

Abstract

Now many image segmentation methods have been studied for extracting the object with the special means but it is difficult to extract only the accurate parameters which can distinguish between images and noises on the noise images. So these methods can not be effective segmentation against the noise images. Therefore it has a problem about the potential decreasing of the performance according to noises for all applications using the present quadtree segmentation. In this paper, we propose an adaptive quadtree segmentation by using the variation and the quartile deviation of the pixels, which can recognize the noises properties and segment effectively the images information on noise images. Therefore our method can be applied for the fields of the various images processing because it has an advantage to distinguish only an image information from the noise images. As the result of our simulation, we confirm that the proposed quadtree segmentation is more efficient than the present quadtree methods when tested on Gaussian noise and impulsive images.