@inproceedings{712a7e78bd914d729f4c11ee765a19f3,
title = "Aliasing removing of hyperspectral image based on fractal structure matching",
abstract = "Due to the richness on high frequency components, hyperspectral image (HSI) is more sensitive to distortion like aliasing. Many methods aiming at removing such distortion have been proposed. However, seldom of them are suitable to HSI, due to low spatial resolution characteristic of HSI. Fortunately, HSI contains plentiful spectral information, which can be exploited to overcome such difficulties. Motivated by this, we proposed an aliasing removing method for HSI. The major differences between proposed and current methods is that proposed algorithm is able to utilize fractal structure information, thus the dilemma originated from low-resolution of HSI is solved. Experiments on real HSI data demonstrated subjectively and objectively that proposed method can not only remove annoying visual effect brought by aliasing, but also recover more high frequency component.",
keywords = "Antialiasing, Fractal structure information, Hyperspectral Image",
author = "Ran Wei and Ye Zhang and Junping Zhang",
note = "Publisher Copyright: {\textcopyright} 2015 SPIE.; Image Sensing Technologies: Materials, Devices, Systems, and Applications II ; Conference date: 22-04-2015 Through 23-04-2015",
year = "2015",
doi = "10.1117/12.2179207",
language = "英语",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
publisher = "SPIE",
editor = "Dutta, \{Achyut K.\} and Dhar, \{Nibir K.\}",
booktitle = "Image Sensing Technologies",
address = "美国",
}