  Scalable image coding for both humans and machines is a technique that has
gained a lot of attention recently. This technology enables the hierarchical
decoding of images for human vision and image recognition models. It is a
highly effective method when images need to serve both purposes. However, no
research has yet incorporated the post-processing commonly used in popular
image compression schemes into scalable image coding method for humans and
machines. In this paper, we propose a method to enhance the quality of decoded
images for humans by integrating post-processing into scalable coding scheme.
Experimental results show that the post-processing improves compression
performance. Furthermore, the effectiveness of the proposed method is validated
through comparisons with traditional methods.
