Multiplierless 16-point DCT Approximation for Low-complexity Image and Video Coding
원문 초록
An orthogonal 16-point approximate discrete cosine transform (DCT) is introduced. The proposed transform requires neither multiplications nor bit-shifting operations. A fast algorithm based on matrix factorization is introduced, requiring only 44 additions---the lowest arithmetic cost in literature. To assess the introduced transform, computational complexity, similarity with the exact DCT, and coding performance measures are computed. Classical and state-of-the-art 16-point low-complexity transforms were used in a comparative analysis. In the context of image compression, the proposed approximation was evaluated via PSNR and SSIM measurements, attaining the best cost-benefit ratio among the competitors. For video encoding, the proposed approximation was embedded into a HEVC reference software for direct comparison with the original HEVC standard. Physically realized and tested using FPGA hardware, the proposed transform showed 35% and 37% improvements of area-time and area-time-squared VLSI metrics when compared to the best competing transform in the literature.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
GANCompress: GAN-Enhanced Neural Image Compression with Binary Spherical Quantization
Enhanced Diagnostic Fidelity in Pathology Whole Slide Image Compression via Deep Learning
FD-LSCIC: Frequency Decomposition-based Learned Screen Content Image Compression
Interleaved Block-based Learned Image Compression with Feature Enhancement and Quantization Error Compensation
Residual Prior-driven Frequency-aware Network for Image Fusion
Perception-Oriented Latent Coding for High-Performance Compressed Domain Semantic Inference
토론
이 논문과 연결된 포럼 글이 아직 없습니다.