  Image compression is an essential and last processing unit in the camera
image signal processing (ISP) pipeline. While many studies have been made to
replace the conventional ISP pipeline with a single end-to-end optimized deep
learning model, image compression is barely considered as a part of the model.
In this paper, we investigate the designing of a fully end-to-end optimized
camera ISP incorporating image compression. To this end, we propose RAWtoBit
network (RBN) that can effectively perform both tasks simultaneously. RBN is
further improved with a novel knowledge distillation scheme by introducing two
teacher networks specialized in each task. Extensive experiments demonstrate
that our proposed method significantly outperforms alternative approaches in
terms of rate-distortion trade-off.
