Image Compression Based On Region Segmentation Algorithm Research And Application

Based on researching of image segmentation theoiy, an efficient image compress algorithm is presented in this paper. Moreover one important application about this algorithm is discussed, and this method is often used in image index based on context. More spatial structure information in images, the image spatial predictors are more efficient. Image segmentation theory just gives a chance to achieve the spatial structure information of images. In addition, this compress algorithm based on image segmentation brings some advantages in image index. In this paper, image compress algorithm and image index based on context are unified by image segmentation theory, and this would maximize the utility of information data. Image segmentation plays a very important role in the algorithm. Not only image compress algorithm is based on it, but also image index based on context is realized through it. Image can be segmented to some regions after compressed by the algorithm based on image segmentation. And each region has its compress parameters, which could be used as key words for image index. As a result, the efficient of image index is improved. Moreover, a user could choose some region to be decompressed if this image is compressed by the algorithm, and he could also examine some region to decide whether this image is required instead of examine the whole image. When this algorithm is used in a net for image index, the image data needed to be transferred could be reduced. This algorithm has synthesized a few important factors in the field of image, and it introduces a very novelty method.