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Sandwiched Image Compression: Increasing the resolution and dynamic range of standard codecs

Phil Chou
Hugues Hoppe
Danhang "Danny" Tang
Ruofei Du
Philip Davidson
2022 Picture Coding Symposium (PCS), IEEE (to appear)

Abstract

Given a standard image codec, we compress images that may have higher resolution and/or higher bit depth than allowed in the codec's specifications, by sandwiching the standard codec between a neural pre-processor (before the standard encoder) and a neural post-processor (after the standard decoder). Using a differentiable proxy for the the standard codec, we design the neural pre- and post-processors to transport the high resolution (super-resolution, SR) or high bit depth (high dynamic range, HDR) images as lower resolution and lower bit depth images. The neural processors accomplish this with spatially coded modulation, which acts as watermarks to preserve the important image detail during compression. Experiments show that compared to conventional methods of transmitting high resolution or high bit depth through lower resolution or lower bit depth codecs, our sandwich architecture gains ~9 dB for SR images and ~3 dB for HDR images at the same rate over large test sets. We also observe significant gains in visual quality.