Hyperspectral data offers a powerful tool for predicting soil heavy metal contamination due to its high spectral resolution
and many continuous bands. However, band selection is the prerequisite to accurately invert and predict soil heavy metal
concentration by hyperspectral data. In this paper, 181 soil samples were collected from the suburb of Nanjing City, and
their reflectance spectra and soil lead concentrations were measured in the laboratory. Based on these dataset, we
compare Least Angle Regression, which is a modest forward choose method, and least squares regression and partial
least squares regression based on genetic algorithm. As a result, regression with band selection has better accuracy than
those without band selection. Although both Least Angle Regression and partial least squares regression with genetic
algorithm can reach 70% training accuracy, the latter based on genetic algorithm is better, because it can reach a larger
solution space. At last, we conclude that partial least squares regression is a good choice for the soil lead content retrieval
by hyperspectral remote sensing data, and genetic algorithm can improve the retrieval by band selection promisingly.
Bands centered around 838nm,1930nm and 2148nm are sensitive for soil lead content.
KEYWORDS: Databases, Visualization, Data modeling, Information visualization, Visual process modeling, Chemical elements, Data storage, Associative arrays, Structural design, Geographic information systems
As a network standard of graphic visualization, SVG (Scalable Vector Graphics) faces an uncompleted representation of
spatial information such as spatial position, spatial relations and map symbols and map decoration. And it's either
impossible to avoid a great capacity of spatial data processing which slowed down the executing speed of the system on
client side. Thus, a SVG-based visualizing database has been proposed as the solution for managing all the graphics and
its attributes of SVG document in a DBMS for Web GIS. The experimental results of the solution shown, 1) it improves
the efficiency of visualizing data transforming and displaying and saves at least half of the implementing time; 2) it
provides an operation in element level based on the designed database structure by selecting the medium granularity as a
storing node; 3) the storing scheme can hold the characteristics of spatial information including spatial position, spatial
relations and map symbols and map decoration by the comparison of both data in document and in the database; 4) it
showed an advantage of the interactive operation with connecting multiply scale of data layers; 5) the database can
creates an externally stored scheme which makes a directly connection between spatial graphic object and joining
attribute database.
This paper presents a fusion method for multi-focus images to produce a new clear image for the scene. First we analyze
the defocused image formation process and obtain a set of ill-posed equations. By imposing some constraints, they
become well-posed and the fusion task is converted to a simple optimization problem. Then the optimization problem,
which minimizes the gradient difference and intensity difference with respect to the objective gradient field and intensity
constraints, is equivalent to the optimal fusion method for multispectral image fusion. So we construct the objective
gradient field and the intensity constraints by clarity analysis and model change respectively and obtain the minimization
result by the iterative optimization steps of optimal fusion. At last, the experiments convincingly demonstrated that the
proposed method has better tolerance to misalignment and noises than wavelet fusion.
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