Coons Surface With Shape Control Parameters In The Image Interpolation

Digital image has become one of the most important information carries in modern life, and it has been applied in every aspects of society life widely. High resolution image is needed in more and more fields. But most digital digitizers can only record images at a resolution lower than desirable. For the limitation of hardware, higher expense will be paid out if hardware is improved on. High resolution image also can not been transmitted directly in net because of limitation of net band broad. So, valid method for image interpolation has become the aim which people are pursuing. In addition, image interpolation is also required when image is calibrated, rotated, mirrored and morphing, etc. Image interpolation is the most important and basal technique in digital image processing.Classical image interpolation methods are all based on classical sampling theory. They approach to perfect low pass filters. 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. The bug in the edge of image will affect the vision effect of image seriously. So, many image interpolation methods all pay attention to improving the edge to improve the vision effect of the whole image.Aiming at the sensitivity of human eyes to edge of image, a self-adapting image interpolation method for edge is presented in this paper. Bicubic Coons surface is introduced to the field of image interpolation. Primal interpolation surface model is founded based on a piecewise bicubic Coons surface. Then five surface shape parameters are introduced, and surface shape is adjusted according to the image edge feature. In this way, the primal interpolation surface model is revised to model with shape parameters. The revised mathematics model can solve edge blue. On the base of precise description of digital image, the interpolation surface is resampled for high resolution image.The numeric experiments prove the validity of this method. This method can achieve preferable results to some image data such as human picture, natural scenery, architectures and remote sensing image. 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.