Cost-efficient super-resolution hardware using local binary pattern classification and linear mapping for real-time 4k conversion

HIGHLIGHTS

  • who: SUNG-HO BAE and colleagues from the Department of Computer Science and Engineering, Kyung Hee University, Yongin-si, South Korea have published the paper: Cost-Efficient Super-Resolution Hardware Using Local Binary Pattern Classification and Linear Mapping for Real-Time 4K Conversion, in the Journal: (JOURNAL)
  • what: The authors propose a new hardware-friendly super-resolution (SR) algorithm using computationally simple feature extraction and regression methods i.e. local binary pattern (LBP) and linear mapping respectively. The authors propose a hardware-friendly SR algorithm and hardware implementation which achieves comparable reconstruction quality of the . . .

     

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