冬小麦红边参数变化规律及其营养诊断

研究了冬小麦冠层光谱红边参数随作物生育期的变化规律,并进行了红边参数与各组分间的相关分析,发现可利用用红边位置反演叶片可溶性糖和叶绿素含量,利用红边振幅反演叶片全氮含量,利用红谷反演叶面积指数。建立了基于红边参数的各组分的统计回归模型,可为生产上利用遥感手段大面积、无破坏、及时评价冬小麦生长状态及营养诊断提供重要依据。     

基于包络线消除的高光谱图像分类方法研究

在高光谱遥感中,包络线消除法一般仅局限于对单个像元的光谱进行光谱分析,从中提取出有助于分类识别的特征波段。而该文则以包络线消除算法为基础,应用VC++语言编程实现了对整个高光谱图像文件去包络、归一化并且提取出分类的特征空间的功能,并且针对原图像文件和去包络线后的图像文件,比较了应用最大似然分类法和光谱角度匹配法进行分类的结果。     

Refinement of wavelength calibrations of hyperspectral imaging data using a spectrum-matching technique

The concept of imaging spectrometry, or hyperspectral imaging, is becoming increasingly popular in scientific communities in recent years. Hyperspectral imaging data covering the spectral region between 0.4 and 2.5 μm and collected from aircraft and satellite platforms have been used in the study of the earth's atmosphere, land surface, and ocean color properties, as well as on planetary missions. In order to make such quantitative studies, accurate radiometric and spectral calibrations of hyperspectral imaging data are necessary. Calibration coefficients for all detectors in an imaging spectrometer obtained in a laboratory may need to be adjusted when applied to data obtained from an aircraft or a satellite platform. Shifts in channel center wavelengths and changes in spectral resolution may occur when an instrument is airborne or spaceborne due to vibrations, and to changes in instrument temperature and pressure. In this paper, we describe an algorithm for refining spectral calibrations of imaging spectrometer data using observed features in the data itself. The algorithm is based on spectrum-matching of atmospheric water vapor, oxygen, and carbon dioxide bands, and solar Fraunhofer lines. It has been applied to real data sets acquired with airborne and spaceborne imaging spectrometers.     

On the dimensionality of multi-view hyperspectral measurements of vegetation

This note investigates the structure of two data sets of highly resolved directional-reflectance of vegetation canopies, obtained with a spectroradiometer mounted on a goniometer. One canopy was a grass lawn (largely erectophile) and the other was of watercress (largely planophile). The data sets consist of radiance measurements in 356 spectral bands in visible and near-infrared wavelengths, and in either 61 or 358 different directions, but avoiding directions very close to the hot-spot. The singular value decompositions of the two-dimensional data sets are used to investigate their intrinsic dimensionality, and so also the redundancy contained in the data. A single directional function and a single spectral function together fit the data quite well in a least squares sense, with the root mean square residual amounting to one part in a hundred of the total sum of squares of the data. However, the residuals indicate that one or two further pairs of functions are needed to characterize the systematic variation of spectral reflectance with direction (or equivalently, of the angular reflectance distribution with wavelength). Three such pairs of functions are found to fit the data to better than one part in a thousand, with the residuals then showing no systematic structure. The consequences for atmospheric correction of multi-view remote sensing data are discussed.     

Mapping of continuous floristic gradients in grasslands using hyperspectral imagery

Transitions between plant species assemblages are often continuous with the form of the transition dependent on the ‘slope’ of environmental gradients and on the style of self-organization in vegetation. Image segmentation can present misleading or even erroneous results if applied to continuous spatial changes in vegetation. Even methods that allow for multiple-class memberships of pixels presuppose the existence of ideal types of species assemblages that constitute mixtures—an assumption that does not fit the case of continua where any section of a gradient is as ‘pure’ as any other section like in modulations of grassland species composition.Thus, we attempted to spatially model floristic gradients in Bavarian meadows by extrapolating axes of an unconstrained ordination of species data. The models were based on high-resolution hyperspectral airborne imagery. We further modelled the distribution of plant functional response types (Ellenberg indicator values) and the cover values of selected species. The models were made with partial least squares (PLS) regression analyses. The realistic utility of the regression models was evaluated by full leave-one-out cross-validation.The modelled floristic gradients showed a considerable agreement with ground-based observations of floristic gradients (R²=0.71 and 0.66 for the first two axes of ordination). Apart from mapping the most important continuous floristic differences, we mapped gradients in the appearance of plant functional response groups as represented by averaged Ellenberg indicator values for soil pH (R²=0.76), water supply (R²=0.66) and nutrient supply (R²=0.75), while models for the cover of single species were weak.Compared to many other vegetation attributes, plant species composition is difficult to detect with remote sensing techniques. This is partly caused by a lack of compatibility between methods of vegetation ecology and remote sensing. We believe that the present study has the potential to increase compatibility as neither spectral nor vegetation information gets lost by a classifying step.     

Performance tests of a new non-invasive sensor unit and ultrasound electronics

Industrial applications involving pulsed ultrasound instrumentation require complete non-invasive setups due to high temperatures, pressures and possible abrasive fluids. Recently, new pulser-receiver electronics and a new sensor unit were developed by Flow-Viz. The complete sensor unit setup enables non-invasive Doppler measurements through high grade stainless steel. In this work a non-invasive sensor unit developed for one inch pipes (22.5 mm ID) and two inch pipes (48.4 mm ID) were evaluated. Performance tests were conducted using a Doppler string phantom setup and the Doppler velocity results were compared to the moving string target velocities. Eight different positions along the pipe internal diameter (22.5 mm) were investigated and at each position six speeds (0.1–0.6 m/s) were tested. Error differences ranged from 0.18 to 7.8% for the tested velocity range. The average accuracy of Doppler measurements for the 22.5 mm sensor unit decreased slightly from 1.3 to 2.3% across the ultrasound beam axis. Eleven positions were tested along the diameter of the 48.4 mm pipe (eight positions covered the pipe radius) and five speeds were tested (0.2–0.6 m/s). The average accuracy of Doppler measurements for the 48.4 mm sensor unit was between 2.4 and 5.9%, with the lowest accuracy at the point furthest away from the sensor unit. Error differences varied between 0.07 and 11.85% for the tested velocity range, where mostly overestimated velocities were recorded. This systematic error explains the higher average error difference percentage when comparing the 48.4 mm (2.4–5.9%) and 22.5 mm (1.3–2.3%) sensor unit performance. The overall performance of the combined Flow-Viz system (electronics, software, sensor) was excellent as similar or higher errors were typically reported in the medical field. This study has for the first time validated non-invasive Doppler measurements through high grade stainless steel pipes by using an advanced string phantom setup.     

Studies on thin film based flexible gold electrode arrays for resistivity imaging in electrical impedance tomography

Practical phantoms are essential to assess the electrical impedance tomography (EIT) systems for their validation, calibration and comparison purposes. Metal surface electrodes are generally used in practical phantoms which reduce the SNR of the boundary data due to their design and development errors. Novel flexible and biocompatible gold electrode arrays of high geometric precision are proposed to improve the boundary data quality in EIT. The flexible gold electrode arrays are developed on flexible FR4 sheets using thin film technology and practical gold electrode phantoms are developed with different configurations. Injecting a constant current to the phantom boundary the surface potentials are measured by a LabVIEW based data acquisition system and the resistivity images are reconstructed in EIDORS. Boundary data profile and the resistivity images obtained from the gold electrode phantoms are compared with identical phantoms developed with stainless steel electrodes. Surface profilometry, microscopy and the impedance spectroscopy show that the gold electrode arrays are smooth, geometrically precised and less resistive. Results show that the boundary data accuracy and image quality are improved with gold electrode arrays. Results show that the diametric resistivity plot (DRP), contrast to noise ratio (CNR), percentage of contrast recovery (PCR) and coefficient of contrast (COC) of reconstructed images are improved in gold electrode phantoms.     

Construction of a head phantom for mixed neutron and gamma field dosimetry in TRR

Boron Neutron Capture Therapy (BNCT) project in Tehran Research Reactor (TRR) is currently ongoing and an appropriate neutron beam for BNCT has been provided by modification of TRR thermal column. In order to measure the neutron beam characteristics inside of a phantom, a standard phantom is needed. The present paper describes details of the head phantom construction and its different potential. The constructed head phantom permits us to put different dosimeters with different sizes in many locations of the phantom volume. Foils, wires, TLDs and ion chamber can be placed inside of its volume. Gel dosimeter can also be poured into the phantom volume and removed from it easily.     

Hyperspectral image compression based on lapped transform and Tucker decomposition

In this paper, we present a hyperspectral image compression system based on the lapped transform and Tucker decomposition (LT-TD). In the proposed method, each band of a hyperspectral image is first decorrelated by a lapped transform. The transformed coefficients of different frequencies are rearranged into three-dimensional (3D) wavelet sub-band structures. The 3D sub-bands are viewed as third-order tensors. Then they are decomposed by Tucker decomposition into a core tensor and three factor matrices. The core tensor preserves most of the energy of the original tensor, and it is encoded using a bit-plane coding algorithm into bit-streams. Comparison experiments have been performed and provided, as well as an analysis regarding the contributing factors for the compression performance, such as the rank of the core tensor and quantization of the factor matrices.     

Non-destructive detection of blackspot in potatoes by Vis-NIR and SWIR hyperspectral imaging

Blackspot is a subsurface potato damage resulting from impacts during harvesting. This type of bruising represents substantial economic losses every year. As the tubers do not show external symptoms, bruise detection in potatoes is not straightforward. Therefore, a nondestructive and accurate method capable of identifying bruised tubers is needed. Hyperspectral imaging (HSI) has been shown to be able to detect other subsurface defects such as bruises in apples. This method is nondestructive, fast and can be fully automated. Therefore, its potential for non-destructive detection of blackspot in potatoes has been investigated in this study. Two HSI setups were used, one ranging from 400 to 1000 nm, named Visible-Near Infrared (Vis-NIR) and another covering the 1000–2500 nm range, called Short Wave Infrared (SWIR). 188 samples belonging to 3 different varieties were divided in two groups. Bruises were manually induced and samples were analyzed 1, 5, 9 and 24 h after bruising. PCA, SIMCA and PLS-DA were used to build classifiers. The PLS-DA model performed better than SIMCA, achieving an overall correct classification rate above 94% for both hyperspectral setups. Furthermore, more accurate results were obtained with the SWIR setup at the tuber level (98.56 vs. 95.46% CC), allowing the identification of early bruises within 5 h after bruising. Moreover, the pixel based PLS- DA model achieved better results in the SWIR setup in terms of correctly classified samples (93.71 vs. 90.82% CC) suggesting that it is possible to detect blackspot areas in each potato tuber with high accuracy.