A novel neural-network-based image resolution enhancement

Her Chang Pu, Chin Teng Lin, Sheng Fu Liang, Nimit Kumar

研究成果: Paper同行評審

2 引文 斯高帕斯(Scopus)


In this paper, a novel HVS-directed neural-network-based adaptive interpolation scheme for natural image is proposed. A fuzzy decision system built from the characteristics of the human visual system (HVS) is proposed to classify pixels of the input image into human perception non-sensitive class and sensitive class. High-resolution digital images along with supervised learning algorithms are used to automatically train the proposed neural network. Simulation results demonstrate that the proposed new resolution enhancement algorithm can produce higher visual quality of the interpolated image than the conventional interpolation methods.

出版狀態Published - 2003
事件The IEEE International conference on Fuzzy Systems - St. Louis, MO, United States
持續時間: 2003 5月 252003 5月 28


OtherThe IEEE International conference on Fuzzy Systems
國家/地區United States
城市St. Louis, MO

All Science Journal Classification (ASJC) codes

  • 軟體
  • 理論電腦科學
  • 人工智慧
  • 應用數學


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