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 25 → 2003 5月 28
|Other||The IEEE International conference on Fuzzy Systems|
|城市||St. Louis, MO|
|期間||03-05-25 → 03-05-28|
All Science Journal Classification (ASJC) codes