New Shape-based Interpolation Of Grey-level Images

With the development of medicine and digital image processing, the accelerating digitization of modern hospital. The digital medical images play a more and more important role in the diagnosis and the treatment of human diseases. But medical images got directly can not satisfy the need of revolution under any situation. In order to improve the revolution and sharpness of the image, we prefer to use software tool than hardware because of the high cost. In addition, image interpolation is the key technology in video image processing, digital cinema, computer animation, computer vision. Therefore image interpolation methods have occupied a peculiar position in medical image processing. So it is need to study image interpolation in application and theory.In the field of the digital image processing, Image interpolation is one of the most and basal technique, the magnifying and the resolution enhancement can be realized by image interpolation, which is very important practically in the sharpness processing and the 3-Ddisplaying.Image interpolation is an important problem Classical image interpolation Method, Such as replication, bilinear interpolation and bicubic spline interpolation and so on, are all based on Nyqusit sampling theory. They approach to perfect low pass filter so high frequency parts are lost, and the quality of image is reduced .In this way the edge of image become blur. Moreover ,the edges of image include the most important information in the image, and it is the one of most important characters in image interpolation methods all pay attention to improving the edge to improve the vision effect of the whole image.Typically, the image data we get are anisotropic, that is, the distance between adjacent image elements within a slice is different from the spacing between adjacent image elements in two neighboring slices. Interpolation is the key to convert such anisotropic data into isotropic one. The traditional interpolation methods include grey-level interpolation and shape-based interpolation. But both of them have their own shortcomings. Grey-level interpolation is easy to blur the object's boundary and shape-based interpolation is nearly limited to binary images only. In this paper, in order to solve these questions, we present a new way to interpolate grey-level images, which is based on the shape of these images. First, we use mathematical morphology to acquire the contour of the interpolated image. To each point in this contour, we find the corresponding points in both original images. According to the acquired grey value of the two corresponding points, we use linear interpolation to calculate the grey value of the interpolated point. Once we acquire each point's gray value, we obtain the final interpolated image. The experimental results show that the new method is effective.Two parts of reverse and reconstruction technology based on CT slice image are mainly studied in this dissertation, which can be concentrated in the following issues:1. CT cross-section scanned image processing, which mainly include image smoothing, image two-valued processing and edge detection. Adjacent-average filter, retaining edge filter and median filter are studied in image smoothing. median filter is used to smooth image; the method of average gray value, the method of maximal entropy, the method of class variance automatic threshold are studied in image segmentation, a new threshold algorithm based on edge feature is presented, the experiment shows that which can keeps the image edge feature well.2. Interpolation of cross-section slice image, because the distance between the two neighboring CT slice images is greater than the distance of neighboring image pixels, this needs to use the method of interpolation to raise the resolution of slice image. In this dissertation, the traditional interpolation methods is studied and analyzed.An interpolation method of object images based on distance transform is presented on the feature of topic, which is interpolating two-valued image between cross-section slice images based on the thought of contour interpolation and shape-based interpolation. The experiment result is good.The numeric experiments prove the validity of this method. This method can achieve preferable results to some image data human picture. Compared with the traditional methods used in the image processing, the results show that the method can improve the smoothness effect of tradition methods greatly and keep the edges of interpolation image still sharp and smooth. This approach offers advantages of taking into account the correlation of the whole image, keeping fine details of image and avoiding the sawtooth effect and smoothing effect associated with raditional image interpolation techniques. The experimental results show that our approach is able to get higher PSNR than existing Interpolation methods in most cases.The research in this dissertation is significant in both theory and real application. The effort to put forward the construction and development of district economy is very important.