Image Compression Brain Image using Matlab

The rapid advancement of high-speed whole-brain imaging techniques poses great challenge for the existing image compression schemes. To accommodate the huge amount of data on limited storage and also facilitate transmission, high compression rates are required, leading to noticeable image degradations that hinder the subsequent scientific observation. In this paper, we propose a deep learning framework for the enhancement of compressed brain images, which learns an efficient post-processing network for the reduction of compression artifacts. This framework is designed for the 3D volumetric brain image with high dynamic range by introducing novel network components, yet it is also applicable to other types of biomedical images. Comprehensive experiments demonstrate the superiority of the proposed method over existing solutions. To the best of our knowledge, this is the first framework for 3D HDR brain image compression with deep enhancement.