English

Low-Complexity Loeffler DCT Approximations for Image and Video Coding

Image and Video Processing 2022-08-01 v1 Computer Vision and Pattern Recognition Multimedia Signal Processing Methodology

Abstract

This paper introduced a matrix parametrization method based on the Loeffler discrete cosine transform (DCT) algorithm. As a result, a new class of eight-point DCT approximations was proposed, capable of unifying the mathematical formalism of several eight-point DCT approximations archived in the literature. Pareto-efficient DCT approximations are obtained through multicriteria optimization, where computational complexity, proximity, and coding performance are considered. Efficient approximations and their scaled 16- and 32-point versions are embedded into image and video encoders, including a JPEG-like codec and H.264/AVC and H.265/HEVC standards. Results are compared to the unmodified standard codecs. Efficient approximations are mapped and implemented on a Xilinx VLX240T FPGA and evaluated for area, speed, and power consumption.

Keywords

Cite

@article{arxiv.2207.14463,
  title  = {Low-Complexity Loeffler DCT Approximations for Image and Video Coding},
  author = {D. F. G. Coelho and R. J. Cintra and F. M. Bayer and S. Kulasekera and A. Madanayake and P. A. C. Martinez and T. L. T. Silveira and R. S. Oliveira and V. S. Dimitrov},
  journal= {arXiv preprint arXiv:2207.14463},
  year   = {2022}
}

Comments

25 pages, 11 figures, 7 tables

R2 v1 2026-06-25T01:19:21.879Z