A Content-Adaptive Up-Sampling Technique for Image Resolution Enhancement

A content adaptive technique is proposed to upsample an image to an output image of higher resolution in this work. The proposed technique is a block-based processing algorithm that offers the flexibility in choosing the most suitable up-sampling method for a particular block type. Block classification is first conducted in the DCT domain to categorized each image block into several types: smooth areas, textures, 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. The unsharp masking method is applied to the textured region to preserve high frequency components. Since human eyes are more sensitive to edges, we adopt a more sophisticated technique to process edge blocks. That is, they are approximated by a facet model so that the image data at subpixel positions can be generated accordingly. A post-processing technique such as ID directional unsharp masking can be used to enhance edge sharpness furthermore. Experimental results are given to demonstrate the efficiency of the proposed technique.