DCT-like Transform for Image Compression Requires 14 Additions Only
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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.
Key facts. Cited by 7 papers in the map (data through 14 Oct 2026). First posted on arXiv 2 Feb 2017.
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Citing papers per year: 2021: 1; 2022: 3; 2023: 1; 2024: 2.
7 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
- 2024Fast Data-independent KLT Approximations Based on Integer Functionscited by 0
- 2024Extensions on Low-complexity DCT Approximations for Larger Blocklengths Based on Minimal Angle Similaritycited by 0
- 2024Extensions on Low-complexity DCT Approximations for Larger Blocklengths Based on Minimal Angle Similarity20 Oct 2024
- 2024Fast Data-independent KLT Approximations Based on Integer Functions11 Oct 2024
- 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