CAJ | 학술논문

对反射光潜数据进行去噪是提高光谱信息准确度的前提.传统时域平滑和频域去噪方法存在诸多缺点,本文首次将广义形态滤波方法用于可见近红外光谱的去噪处理,并提出基于小波包变换和数学形态学结合的光谱去噪方法.使用USGS光谱库中的植被光谱进行实验,采用信噪比(SNR)、均方误差根(RMSE)、波形相似度(NCC)和平滑度(SR)四个指标来评估去噪效果.结果表明,小波包最佳基阈值法和广义形态滤波法都能较好地保持波形和平滑度,广义形态滤波法能较好地消除幅值较大的随机噪声,但其对连续随机噪声中幅值较小的噪声成分不能有效消除;而小波包最佳基阈值法不能有效消除幅值较大的噪声成分;二者结合的方法组合了这两者的优点,使得幅值较大、较小的噪声成分都能较好地消除,同时还提高了相似度和平滑度指标,充分表明小波包最佳基阈值与广义形态滤波结合的方法是一种更好的可见光近红外光谱去噪方法.
대반사광잠수거진행거조시제고광보신식준학도적전제.전통시역평활화빈역거조방법존재제다결점,본문수차장엄의형태려파방법용우가견근홍외광보적거조처리,병제출기우소파포변환화수학형태학결합적광보거조방법.사용USGS광보고중적식피광보진행실험,채용신조비(SNR)、균방오차근(RMSE)、파형상사도(NCC)화평활도(SR)사개지표래평고거조효과.결과표명,소파포최가기역치법화엄의형태려파법도능교호지보지파형화평활도,엄의형태려파법능교호지소제폭치교대적수궤조성,단기대련속수궤조성중폭치교소적조성성분불능유효소제;이소파포최가기역치법불능유효소제폭치교대적조성성분;이자결합적방법조합료저량자적우점,사득폭치교대、교소적조성성분도능교호지소제,동시환제고료상사도화평활도지표,충분표명소파포최가기역치여엄의형태려파결합적방법시일충경호적가견광근홍외광보거조방법.
The present study introduced the generalized morphological filter into the denoising of visible and near infrared spectra for the first time，and provided a new method for denoising the reflectance spectra by combining mathematical morphology methods with the wavelet packet transformation.The authors used vegetable spectra from USGS spectral library as the reference spectra，and obtained the noised spectra by adding noises with different signal-to-noise ratios to the referenced spectra.The resuits were evaluated by signal-to-noise ratio (SNR)，root mean squared error (RMSE)，normalized correlation coefficient (NCC) and smoothness ratio (SR) of the denoised spectra.The authors'results showed that both the thresholding on wavelet packet decomposition best bases method and the generalized morphological filter method could maintain the spectral shape and the spectral smoothness after denoising.The generalized morphological filter method can remove larger amplitude random noise whereas the continuous small amplitude random noise could not be removed well.Hence，the denoised spectra were not smooth.Nevertheless，the denoised spectra using the thresholding on the best base groups of wavelet packet decomposition method were smooth，but the larger amplitude noise could not be removed completely.The authors'method by combining the two methods has the merits of the two methods but removing their defects.The results showed that both large and small amplitude noise could be removed completely，meanwhile the normalized correlation coefficient (NCC) and smoothness ratio (SR) were improved，which indicated that the authors' method is superior to other methods in denoising visible and near infrared spectra.