  Trit-plane coding enables deep progressive image compression, but it cannot
use autoregressive context models. In this paper, we propose the context-based
trit-plane coding (CTC) algorithm to achieve progressive compression more
compactly. First, we develop the context-based rate reduction module to
estimate trit probabilities of latent elements accurately and thus encode the
trit-planes compactly. Second, we develop the context-based distortion
reduction module to refine partial latent tensors from the trit-planes and
improve the reconstructed image quality. Third, we propose a retraining scheme
for the decoder to attain better rate-distortion tradeoffs. Extensive
experiments show that CTC outperforms the baseline trit-plane codec
significantly in BD-rate on the Kodak lossless dataset, while increasing the
time complexity only marginally. Our codes are available at
https://github.com/seungminjeon-github/CTC.
