State-of-the-art video coding techniques employ block-based
illumination compensation to improve coding efficiency. In
this work, we propose a Lifting-based Illumination Adaptive
Transform (LIAT) to exploit temporal redundancy among
frames that have illumination variations, such as the frames
of low frame rate video or multi-view video. LIAT employs
a mesh-based spatially affine model to represent illumination
variations between two frames. In LIAT, transformed frames
are jointly compressed, together with illumination information,
into a layered rate-distortion optimal codestream, using
the JPEG2000 format. We show that the LIAT framework significantly
improves compression efficiency of temporal subband
transforms for both predictive and more general transforms
with predict and update steps.