Learning True Rate-Distortion-Optimization for End-To-End Image Compression. (arXiv:2201.01586v1 [eess.IV])

Even though rate-distortion optimization is a crucial part of traditional
image and video compression, not many approaches exist which transfer this
concept to end-to-end-trained image compression. Most frameworks contain static
compression and decompression models which are fixed after training, so
efficient rate-distortion optimization is not possible. In a previous work, we
proposed RDONet, which enables an RDO approach comparable to adaptive block
partitioning in HEVC. In this paper, we enhance the training by introducing
low-complexity estimations of the RDO result …

arxiv compression learning optimization rate