Abstract
As large screen display devices become popular, people ask high-resolution images. However, due to the limitation of the digital image cameras, the captured images tend to be the low-resolution images. If we display these low-resolution images on a high-resolution display device, we must use a super-resolution technique of the image processing. The image interpolation is one common technique to do super-resolution. The traditional image interpolation techniques have many problems, such as the blurring edges or jaggies on the edge region, therefore reduces the visual quality of the image. In our thesis, we proposed a simple edge direction detection method which classifies the local information of a missing pixel into five categories when we want to interpolate it for a high-resolution image. According to its type of edge direction we designed five templates of the reference pixels. Finally, we proposed a nonlinear interpolation algorithm which combines the geometric distance weight and patch similarity weight to determine an optimal weight for every reference pixel. Through the weighted sum of all reference pixels then we interpolate the missing pixels. The experiment result shows that no matter any direction of the edges, the proposed algorithm can obtain sharper edges and clear visual quality than other methods, and it also can increase the PSNR. Key word: super-resolution, edge direction detection, templates of the reference pixels, nonlinear interpolation