Estimation of Paddy Rice Leaf Area Index Using Digital Photography

被引：0

作者：

Ge, Yunjian ^{[1
]}

Liu, Zhenbo ^{[1
]}

Chen, Jian ^{[1
]}

Sun, Tao ^{[2
]}

机构：

[1] Nanjing Univ Informat Sci & Technol, Sch Remote Sensing, Nanjing, Jiangsu, Peoples R China

[2] Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing, Peoples R China

来源：

2014 7TH INTERNATIONAL CONGRESS ON IMAGE AND SIGNAL PROCESSING (CISP 2014) | 2014年

关键词：

Digital Images; Gamma Correction; Leaf Area Index; Paddy Rice Canopy; VEGETATION INDEXES; CAMERAS; COVER; MODEL; WHEAT;

D O I：

暂无

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

In imaging process of digital cameras, digital number (DN) of images is often automatically compensated for effectiveness of human vision. In this study, DN correction based on gamma transformation theory is combined with a look-up table method to convert the output DN into a calibrated digital number (cDN). Then, the leaf area index (LAI) of paddy rice is estimated from gap fraction measurement in the vertical direction using the top-of-canopy digital color photography of rice and compare with the LAI measured using LAI-2000 instrument. The results show that the use of cDN improves the accuracy of estimated LAI due to its more precise differentiation between green leaf area and background in the histogram of corrected images, as well as less influence to LAI estimation from the water background of paddy rice in the early growing season and ears of rice and withered leaves during the late growing season.

引用

页码：681 / 686

页数：6

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