Pretreatment of Aircraft Spectrum in Visible and Near Infrared Band Based on Wavelet Transform

Yihong Zhang, Wenjie Zhao, Jituo Shi
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引用次数: 1

Abstract

In recent years, the rapid improvement of spectral resolution has brought about the explosive growth of spectral data, and the spectral characteristics of ground objects have been expressed in more detail. Different substances can be distinguished according to the spectral curves. However, the spectral curve obtained from the measurement is often accompanied by inevitable noise interference. In this paper, the pretreatment method of aircraft spectral curve based on wavelet transform was studied to find out the best combination of wavelet parameters suitable for aircraft spectral data to remove dark current noise, and to suppress the interference of environmental noise by envelope removal method. In this paper, a new threshold function was proposed, which avoided the loss of features caused by constant compression and the difficulty of parameter selection in traditional threshold denoising. Combining with minimaxi threshold criterion, 4-layer decomposition level and sym8 wavelet, the new threshold function achieved optimal denoising performance which was much better than that of the four common filtering methods.
基于小波变换的飞机可见光和近红外光谱预处理
近年来,光谱分辨率的快速提高带来了光谱数据的爆炸式增长,地物的光谱特征得到了更详细的表达。根据光谱曲线可以区分不同的物质。然而,测量得到的光谱曲线往往伴随着不可避免的噪声干扰。本文研究了基于小波变换的飞机频谱曲线预处理方法,找出适合飞机频谱数据的小波参数的最佳组合,以去除暗电流噪声,并通过包络去除方法抑制环境噪声的干扰。本文提出了一种新的阈值函数,避免了传统阈值去噪中不断压缩造成的特征丢失和参数选择困难的问题。结合极大极小阈值准则、四层分解层次和sym8小波,该阈值函数达到了最优的去噪效果,大大优于常用的四种滤波方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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