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Vegetation field spectrum denoising via lifting wavelet transform
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作者 周广柱 杨锋杰 王翠珍 《Journal of Coal Science & Engineering(China)》 2008年第1期131-135,共5页
Field spectrum pretreatment experiments were carried out, and denoising numerical experiment via lifting wavelet transform (LWT) was designed, and several famous test signals including blocks, bumps, heavy sine and ... Field spectrum pretreatment experiments were carried out, and denoising numerical experiment via lifting wavelet transform (LWT) was designed, and several famous test signals including blocks, bumps, heavy sine and doppler were processed via Lw'r in these experiment. And the field spectrum was processed via Lw'r. Experiments proved that SNRG-tO-SNRN curves have similar feature and they all have a peak. And SNRG of almost all employed wavelets have higher value with SNRN between 0 and 20 dB. When signal is at high SNR, the SNRG is very little, and the MSED of denoised signal became little by little. LWT is more suite to denoise the low SNR or heavy noise contaminated signals. Bior4.4 have wider SNRN interval for denoising comparing with other five wavelets, includ- ing haar, db6, sym6, bior2.2 and bior3.3. Original field spectrum is processed by 3 stage liftings based on bior4.4 to denoise the trivial noise-contaminated regions. On processing the water band signal, logarithm transform is firstly taken. And then the spectrum is denoised via LWT based on bior4.4. The results show that an excellent denoised spectrum can be get, especially between 350 nm and 1 800 nm, and between 1 960 nm to 2 500 nm. While there is still a bump around 1 900 nm, this maybe due to the spectrum machine's limited precision. 展开更多
关键词 vegetation field spectrum lifting wavelet transform DENOISE numerical ex-periment
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Inversion of Biochemical Parameters by Selection of Proper Vegetation Index in Winter Wheat 被引量:2
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作者 HUANGWen-jiang WANGJi-hua +3 位作者 LIULiang-yun ZHAOChun-jiang WANGZhi-jie WANGJin-di 《Agricultural Sciences in China》 CAS CSCD 2004年第3期178-185,共8页
Recent studies have demonstrated the application of vegetation indices from canopy reflectedspectrum for inversion of chlorophyll concentration. Some indices are both response tovariations of vegetation and environmen... Recent studies have demonstrated the application of vegetation indices from canopy reflectedspectrum for inversion of chlorophyll concentration. Some indices are both response tovariations of vegetation and environmental factors. Canopy chlorophyll concentration, anindicator of photosynthesis activity, is related to nitrogen concentration in green vegetationand serves as an indicator of the crop response to soil nitrogen fertilizer application. Thecombination of normalized difference vegetation index (NDVI) and photochemical reflectanceindex (PRI) can reduce the effect of leaf area index (LAI) and soil background. The canopychlorophyll inversion index (CCII) was proved to be sensitive to chlorophyll concentration andvery resistant to the other variations. This paper introduced the ratio of TCARI/OSAVI to makeaccurate predictions of winter wheat chlorophyll concentration under different cultivars. Itindicated that canopy chlorophyll concentration could be evaluated by some combined vegetationindices. 展开更多
关键词 Winter wheat Canopy reflected spectrum Structure Insensitive vegetation Index Chlorophyll concentration
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