.png){kind=icon}
.png){kind=icon}
Return
A Deterministic Low-Complexity Approximate (Multiplier-Less) Technique for DCT Computation
.png){kind=icon}
PRE
AI
DOI：10.1109/TCSI.2019.2902415.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
The approximate (multiplier-less) two-dimensional discrete cosine transform (DCT) is a widely adopted technique for image/video compression. This paper proposes a deterministic low-complexity approximate DCT technique that accurately configures the size of the transform matrix (T) according to the number of retained coefficients in the zigzag scanning process. This is achieved by establishing the relationship between the number of retained coefficients and the number of rows of the T matrix. The proposed technique referred to as the zigzag low-complexity approximate DCT (ZLCADCT), when compared with approximate DCT (ADCT), decreases the number of addition operations and the energy consumption while retaining the PSNR of the compressed image. In addition, the ZLCADCT eliminates the zigzag scanning process used in the ADCT. Moreover, to characterize the deterministic operation of the ZLCADCT, a detailed mathematical model is provided. A hardware platform based on FPGAs is then utilized to experimentally assess and compare the proposed technique; as modular, deterministic, low latency, and scalable, the proposed techniques can be implemented upon any change in the number of retaining coefficients by realizing only a partial reconfiguration of the FPGA resources for the additional required hardware. The extensive simulation and experimental results show the superior performance compared to previous ADCT techniques under different metrics.
Keywords:
Approximate DCT
addition
FPGA
low power DCT
zigzag scanning
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
5.2
Papers:
9.7K
Citations:
2.2W