A Class of Low-complexity DCT-like Transforms for Image and Video Coding

TL;DR

This paper introduces a new class of low-complexity, multiplierless DCT-like transforms for image and video coding, offering a good balance between computational efficiency and coding performance, suitable for real-time and low-power applications.

Contribution

It proposes a multiparametric transform class including RDCT and MRDCT, along with four new orthogonal low-complexity 8-point DCT approximations, and extends these to longer lengths with efficient algorithms.

Findings

Transforms perform close to or better than state-of-the-art DCT approximations.

Proposed methods are effective in image and video coding experiments.

Transforms are suitable for hardware implementation in real-time applications.

Abstract

The discrete cosine transform (DCT) is a relevant tool in signal processing applications, mainly known for its good decorrelation properties. Current image and video coding standards -- such as JPEG and HEVC -- adopt the DCT as a fundamental building block for compression. Recent works have introduced low-complexity approximations for the DCT, which become paramount in applications demanding real-time computation and low-power consumption. The design of DCT approximations involves a trade-off between computational complexity and performance. This paper introduces a new multiparametric transform class encompassing the round-off DCT (RDCT) and the modified RDCT (MRDCT), two relevant multiplierless 8-point approximate DCTs. The associated fast algorithm is provided. Four novel orthogonal low-complexity 8-point DCT approximations are obtained by solving a multicriteria optimization problem. The optimal 8-point transforms are scaled to lengths 16 and 32 while keeping the arithmetic complexity low. The proposed methods are assessed by proximity and coding measures with respect to the exact DCT. Image and video coding experiments hardware realization are performed. The novel transforms perform close to or outperform the current state-of-the-art DCT approximations.