An Integer Approximation Method for Discrete Sinusoidal Transforms
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Abstract (arXiv)
Approximate methods have been considered as a means to the evaluation of discrete transforms. In this work, we propose and analyze a class of integer transforms for the discrete Fourier, Hartley, and cosine transforms (DFT, DHT, and DCT), based on simple dyadic rational approximation methods. The introduced method is general, applicable to several block-lengths, whereas existing approaches are usually dedicated to specific transform sizes. The suggested approximate transforms enjoy low multiplicative complexity and the orthogonality property is achievable via matrix polar decomposition. We show that the obtained transforms are competitive with archived methods in literature. New 8-point square wave approximate transforms for the DFT, DHT, and DCT are also introduced as particular cases of the introduced methodology.
Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). First posted on arXiv 5 Jul 2020.
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Citing papers per year: 2021: 1; 2022: 3; 2023: 1.
5 papers.
- 2021Low-complexity Rounded KLT Approximation for Image Compressioncited by 2
- 2022DCT Approximations Based on Chen's Factorizationcited by 1
- 2022Low-complexity Approximate Convolutional Neural Networkscited by 1
- 2023Low-complexity Multidimensional DCT Approximationscited by 1
- 2022Low-Complexity Loeffler DCT Approximations for Image and Video Codingcited by 0
- 2023Low-complexity Multidimensional DCT Approximations20 Jun 2023
- 2022Low-complexity Approximate Convolutional Neural Networks29 Jul 2022
- 2022Low-Complexity Loeffler DCT Approximations for Image and Video Coding29 Jul 2022
- 2022DCT Approximations Based on Chen's Factorization24 Jul 2022
- 2021Low-complexity Rounded KLT Approximation for Image Compression28 Nov 2021