# DCT-like Transform for Image Compression Requires 14 Additions Only

arXiv: https://arxiv.org/abs/1702.00817 · HTML: https://mlsanity.com/paper/1702.00817/

## Key facts

- Cited by 7 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 2 Feb 2017.

## Built on by (most cited first, 7 of 7)

- [Low-complexity Rounded KLT Approximation for Image Compression](https://mlsanity.com/paper/2111.14239/) (2021)
- [DCT Approximations Based on Chen's Factorization](https://mlsanity.com/paper/2207.11638/) (2022)
- [Low-complexity Approximate Convolutional Neural Networks](https://mlsanity.com/paper/2208.00087/) (2022)
- [Low-complexity Multidimensional DCT Approximations](https://mlsanity.com/paper/2306.11724/) (2023)
- [Low-Complexity Loeffler DCT Approximations for Image and Video Coding](https://mlsanity.com/paper/2207.14463/) (2022)
- [Fast Data-independent KLT Approximations Based on Integer Functions](https://mlsanity.com/paper/2410.09227/) (2024)
- [Extensions on Low-complexity DCT Approximations for Larger Blocklengths Based on Minimal Angle Similarity](https://mlsanity.com/paper/2410.15244/) (2024)

## Abstract (arXiv)

A low-complexity 8-point orthogonal approximate DCT is introduced. The proposed transform requires no multiplications or bit-shift operations. The derived fast algorithm requires only 14 additions, less than any existing DCT approximation. Moreover, in several image compression scenarios, the proposed transform could outperform the well-known signed DCT, as well as state-of-the-art algorithms.