Subpixel-based down-sampling via Min-Max Directional Error

Abstract

Subpixel-based down-sampling is a method that can potentially improve the apparent resolution of a down-scaled image by controlling individual subpixels rather than pixels. However, the increased luminance resolution often comes at the expense of chrominance distortion. In this paper, we formulate the subpixel-based down-sampling as a Min-Max problem (Min-Max Directional Error) which we call MMDE. Unfortunately, the solution of MMDE is computational intensive, especially for large images. We thus relax the MMDE by determining the maximum error based on HVS, which largely reduces the number of constraints. We call such relaxation as MMDE-VR (Visual Relaxation). Simulation results illustrate that MMDE-VR can effectively reduce visible color fringing artifacts while still maintaining sharpness.