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2X Super-Resolution Hardware Using Edge-Orientation-Based Linear Mapping for Real-Time 4K UHD 60 fps Video Applications.
- Source :
- IEEE Transactions on Circuits & Systems. Part II: Express Briefs; Sep2018, Vol. 65 Issue 9, p1274-1278, 5p
- Publication Year :
- 2018
-
Abstract
- Based on our previous super-interpolation method, we propose a novel hardware-friendly super-resolution (SR) algorithm, called HSI method, and its dedicated hardware architecture for up-scaling full-high-definition (FHD) video streams to 4K ultra-high-definition (UHD) video streams in real-time. Our proposed HSI method involves training and up-scaling steps. In the training step, an edge-orientation-based clustering is applied for low-resolution (LR) training patches to obtain a training patch set for each class, and a linear mapping kernel is learned from LR to high-resolution (HR) based on the training patch set for each class. In the up-scaling step, each LR input patch is transformed to an HR patch by applying the linear mapping kernel for its class. We implemented the up-scaling step of our HSI method by a dedicated hardware (HW) with the pre-trained linear mapping kernels stored in a look-up table. Our HW implementation, called HSI HW, contains 159K gate counts and achieves about 880 Mpixels/s throughput by using the TSMC 0.13-um CMOS process, and thus performing the SR operation from FHD to 4K UHD in real-time. Compared with conventional SR methods, our HW implementation of HSI reconstructs HR images of higher peak signal to noise ratio values and better visual quality. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 15497747
- Volume :
- 65
- Issue :
- 9
- Database :
- Complementary Index
- Journal :
- IEEE Transactions on Circuits & Systems. Part II: Express Briefs
- Publication Type :
- Academic Journal
- Accession number :
- 131487382
- Full Text :
- https://doi.org/10.1109/TCSII.2018.2799577