摘要
文章深入分析了高光谱遥感数据中噪声的特点,提出了一种基于平稳小波变换的改进小波滤噪算法。通过对标准图像和PHI高光谱遥感数据实验,证明此方法具有比软阈值方法更好的抑制噪声和保持信号细节的能力,并能良好地拟合高光谱数据中噪声随波长的复杂变化,改善数据处理的效果。
This paper analyzed the characteristic of noise in hyperspectral data deeply, and puts forward a de-noising method based on stationary discrete wavelet transform(SDWT). Based on the experiment to standard image and hyperspectral data, it is proved that this method can eliminate noise and keep detail better than soft-threshold wavelet de-noising method. Furthermore, this method can excellently fit the complex variety of noise in hyperspectral data with wavelengh, improving the results of processing.
出处
《信息工程大学学报》
2005年第2期91-95,共5页
Journal of Information Engineering University
基金
国家863计划资助项目(2002AA783050)
关键词
平稳小波变换
阈值滤噪
高光谱
stationary discrete wavelet transform(SDWT)
threshold-denoising
hyperspectral
