Segmented image interpolation using edge direction and texture synthesis

In this paper, we propose an adaptive interpolation method for low quality still images such as single video frames. Our method chooses different interpolation schemes according to the local image context. First, we segment the image into three types of regions: smooth regions which contain no edges, well-defined edges such as object boundaries, and textured regions which are covered by dense spurious edges. For smooth regions, we simply apply bilinear interpolation. For the well-defined edges, we develop an edge-directed interpolation scheme. For the remaining textured regions, we apply a residual error estimation method to enhance the high frequency components, hence improving the visual sharpness of these regions. Our results show a visible improvement compared to images generated by traditional interpolation methods, with sharp edges, enhanced textures, and low noise level in smooth regions.

1. INTRODUCTION

Digital image interpolation is a widely used technique in image printing. When images from some low quality sources such as video sequences are to be printed, we face two challenges. On the one hand, video images are generally more blurred than those pictures captured by digital cameras. On the other hand, printing these images usually requires a large scaling factor. For example, printing a CIF video image on regular inch photo paper requires a scaling factor of 4 with a printing resolution of 300 dpi, or a scaling factor of 8 with a higher printing resolution of 600 dpi.