Abstract
This study proposes a subpixel-based image downsampling algorithm using content-adaptive two-dimensional (2D) finite impulse response (FIR) filters. The proposed algorithm consists of a learning stage and an inference stage. In the learning stage, using a sufficient number of low-resolution (LR) and high-resolution (HR) patch pairs, the authors compute optimal 2D FIR filters to synthesise LR patches of the highest quality from a specific HR patch and store the patch-adaptive 2D FIR filters in a dictionary. In the inference stage, they explore candidates that best match to each HR input patch in the dictionary and synthesise LR patches by using their corresponding 2D FIR filters on a subpixel basis. The experimental results show that the proposed algorithm produces higher-quality LR images on a patch basis than existing methods and entails no blur and aliasing artefacts.
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