Abstract
Lossy compression algorithms aim to compactly encode
images in a way which enables to restore them with minimal
error. We show that a key limitation of existing algorithms
is that they rely on error measures that are extremely sensitive to geometric deformations (e.g. SSD, SSIM). These
force the encoder to invest many bits in describing the exact
geometry of every fine detail in the image, which is obviously wasteful, because the human visual system is indifferent to small local translations. Motivated by this observation, we propose a deformation-insensitive error measure
that can be easily incorporated into any existing compression scheme. As we show, optimal compression under our
criterion involves slightly deforming the input image such
that it becomes more “compressible”. Surprisingly, while
these small deformations are barely noticeable, they enable
the CODEC to preserve details that are otherwise completely lost. Our technique uses the CODEC as a “black
box”, thus allowing simple integration with arbitrary compression methods. Extensive experiments, including user
studies, confirm that our approach significantly improves
the visual quality of many CODECs. These include JPEG,
JPEG 2000, WebP, BPG, and a recent deep-net method