An efficient upsampling technique for images and videos

Abstract

A block-based upsampling method for images and videos is proposed in this work. Block classification is first conducted in the DCT domain to categorize 8x8 image blocks into several types: smooth areas, edges and others. For the plain background and smooth surfaces, simple patches are used to enlarge the image size without degrading the resultant visual quality. Since human eyes are more sensitive to edges, a more sophisticated technique is applied to edge blocks. They are approximated by a facet model so that the image data at subpixel positions can be generated accordingly. By taking temporal information into account, this concept can further be applied to videos. To upsample an image block in the current frame, we may borrow the upsampled version of the corresponding block in the reference frame if the residual is tolerable. Experimental results are shown to demonstrate the great reduction of computational complexity while the output visual quality still remains satisfactory. © 2009 Springer-Verlag Berlin Heidelberg.