Efficient JPEG2000 EBCOT Context Modeling for Massively Parallel Architectures

Embedded Block Coding with Optimal Truncation (EBCOT) is the fundamental and computationally very demanding part of the compression process of JPEG2000 image compression standard. In this paper, we present a reformulation of the context modeling of EBCOT that allows full parallelization for massively parallel architectures such as GPUs with their single instruction multiple threads architecture. We prove that the reformulation is equivalent to the EBCOT specification in JPEG2000 standard. Behavior of the reformulated algorithm is demonstrated using NVIDIA CUDA platform and compared to other state-of-the-art implementations.