Low Complexity Embedded Compression Algorithm for Reduction of Memory Size and Bandwidth Requirements in the JPEG2000 Encoder

In this paper, a new and low-complexity embedded compression (EC) algorithm for the JPEG2000 encoder system is proposed to efficiently reduce memory requirements. The proposed EC algorithm is used to achieve a fixed compression ratio of 50% under the near-lossless-compression constraint. Through the EC technique, the memory requirement for intermediate low-frequency coefficients during multiple DWT stages can be reduced by a factor of 2 compared with direct implementation of the JPEG2000 encoder. By jointly considering the coding flow of both block-based 2D-DWT and bit-plane coders, the EC scheme combines an efficient quantization and simple entropy coder to reduce memory transaction bandwidth between DWT and bit-plane coder (BPC) to 50%. Furthermore, this EC reduces the size of code-block memory from DWT to BPC. Experiment results based on standard test image benchmarks show that our proposed EC algorithm presents only PSNR degradation of 1.05 dB on average when the target compression ratio is fixed at 50%. Our EC can be applicable to the JPEG2000 encoding system to save memory size and bandwidth requirements with minor picture quality degradation. The proposed EC algorithm is also computationally simple, reducing latency time and creating sufficient accessibility(1).