Abstract:Abnormal behaviors were observed in magnetic circular dichroism (MCD) in both as-grown and annealed Ga0.95Mn0.05As/InGaAs epilayer, as the direction of magnetization vector turns away from or toward the direction of incident beam by applying a magnetic field. Following the mean-field theory of magnetocrystalline anisotropy, it is found that the phenomena are actually the manifestation of the influence of the magnetic anisotropy on interband optical transitions due to the dependence of hole band splitting and warp of E-k dispersion relation on the magnetization orientation.

Abstract:Ge2Sb2Te5 (GST) alloy films on Si (100) substrate was prepared by a magnetron sputtering system at room temperature. The samples irradiated by femtosecond laser with different energy or annealed at 200℃ in an annealing furnace were studied by Raman spectra measurement, respectively. The dynamic transformation from amorphous state to crystalline state of GST films was analyzed by the changes of their Raman spectra. With the increasing of the laser intensity irradiated on the samples, regular shifts of their Raman peaks were found. Furthermore, the Raman spectra of the samples annealed at 200℃ are similar to that of irradiated by femtosecond laser with intensity of 24 mJ/cm2. The phase change caused by ultrafast laser irradiation is similar to the thermal treatment in this case.

Abstract:Soil moisture was one of the most important parameters characterizing surface dryness conditions. Its retrieval by quantitative remote sensing methods had been a challenging problem. By analyzing the sensitivity of shortwave infrared MODIS band 6 and band 7 to the changes of water, the MODIS shortwave infrared spectral feature space was constructed. According to the soil moisture variation in spectral feature space, a simple and practical MODIS shortwave infrared soil moisture index (SIMI) was put forward and validated using ground-measured 0~10cm averaged soil moisture of Ningxia plain. The results show that the coefficient of determination (R2) of both them varies from 0.39 to 0.58, and SIMI has higher accuracy than temperature-vegetation index (TVX) for soil moisture retrieval. These results support the reliability of this index for regional soil moisture retrieval. However, SIMI does not eliminate the impact of mixed-pixels and still needs further improvement and perfection.

Abstract:he equation that describes the effect of phase relation of the sequence images on the super resolution image reconstruction was summarized. The amplification of Gaussian noise and shot-noise raised by super resolution image reconstruction was studied. Wiener Filter can restrain the amplified Gaussian noise effectively after super resolution image reconstruction. The shot noise, however, becomes ripple noise after image reconstruction. This brings image confusion because that traditional median filter can not restrain the ripple noise. Considering that the images processed are in sequence, a method of median filter based on sequence images was proposed. The pixels with noise, determined by pleonastic information in sequence images, were eliminated by median filter while the pixels without noise were kept untouched. Median filter based on sequence images restrains noise more powerfully than the one based on single image. It does not bring image confusion and thus improves the quality of the image.

Abstract:Beginning with the analysis of the real-time performance and robustness of scale-invariant feature transform (SIFT), the paper optimized traditional algorithm in both aspects of matching time and accuracy. A multi-scale feature extraction algorithm was proposed which is based on moving target. This algorithm was devised in two improved ways. One way was that the size of the template could automatically adjust along with the change of the scale factor. The other was that a bidirectional feature points matching was introduced into the algorithm. With the improved algorithm, the weakness of the real-time performance and robustness was amended successfully for match between the images and the moving target. Finally, experiment showed that with the improved algorithm, the sequential frame images based on time-axis could be matched quickly and accurately.

Abstract:Because of the local minima in the objective function, the traditional Nonnegative Matrix Factorization (NMF) algorithm is sensitive to the initial value when being applied to hyperspectral unmixing. In order to solve the problem, a new approach based on constrained NMF was proposed for decomposition of mixed pixels by introducing constraints of abundance separation and smoothness into the objective function of NMF. The algorithm can also satisfy the abundance nonnegative and sum-to-one constraints, which are necessary for hyperspectral unmixing. Experimental results on simulated and real hyperspectral data demonstrate that the proposed approach can overcome the shortcoming of local minima, and obtain better results. Meanwhile, the algorithm performs well for noisy data, and can also be used for the unmixing of hyperspectral data in which pure pixels do not exist.

Abstract:An integrated 2mm band sub-harmonic mixer based on quartz circuits was presented. General harmonic mixer theory was introduced. The equivalent circuit model for the anti-pair diodes was built. Then the extensive simulation and optimization by the full wave analysis software were done. When the 59GHz LO signal’s power was set between 7~14dBm, the mixer yielded a least conversion loss of 17dB and a maximum loss less than 20dB under working frequency of 116~120GHz. The P1dB of the mixer is about 1dBm. The isolation between the three ports is better than 20dB.The measured results of the sub-harmonic mixer are agreed well with the simulated ones.

Abstract:For measuring insertion loss, reflection and radiation of smoke screen, a 3mm wave electromagnetic characteristic measurement radar has been fabricated, which comprises a 3mm wave radar cross section (RCS) measurement radar and a 3mm wave radiometer. The transmitter and receiver of the former are separated, and each antenna of them can be chosen among three kinds of antennas with different beam width or gain, according to the sizes of object and the power of reflection signal. In order to fit the tremendous changes of power between transmission and reflection, the sensitivity and the dynamic range of the system is improved by millimeter wave fixed attenuator, switching between long range and short range, and digital intermediate frequency (IF) receiver with signal accumulating by Fast Fourier Transform Algorithm (FFT). In the 3mm wave super-heterodyne IF Dicke-radiometer, hardware integral and soft integral are both used to achieve high sensitivity. All the millimeter wave oscillators in the system are phase-locked. The interval between two adjacent data is 2ms, which is suitable for suspending and movable smoke screen.

Abstract:The infrared radiation transfer should be considered together with other heat transfer process in the phase change of the semitransparent medium. Solidification heat transfer via absorbing, emitting and isotropically scattering in 2-D rectangular semitransparent medium were analyzed. Solidification was assumed to occur over a range of temperatures, and liquid-, mushy- and solid-zones were considered. The enthalpy-based energy equation was solved by the finite volume method. The infrared radiation transfer was solved by the Monte-Carlo method. The results of 1-D phase change heat conduction and 2-D transient coupled infrared radiation and conduction were in good agreements with published data. Effects of various parameters, such as extinction coefficient, refractive index, conduction-radiation parameter and latent heat, et al., on temperature and liquid fraction distributions in the medium were studied. Some of these thermal optical property parameters were found to have significant effects on the results.

Abstract:For the rapid detection of leaf nitrogen content of summer corn, visible and near infrared (Vis/NIR) spectra of summer corn leaves, with different nitrogen levels at spinning stage, were measured by an ASD FieldSpec. Discrete approximation wavelet coefficient vectors of the second-scale were obtained via logarithmic transformation and multi-scale wavelet decomposition of the spectra data within “near infrared spectrum platform” (760~1000nm) and “green peak” (450~ 680nm). Then principal components (PCs) were selected from these vectors by principal component analysis (PCA), and used as inputs of a generalized regression neural network (GRNN). The model was employed for the prediction of leaf nitrogen content of summer corn. Results show that logarithmic transformation can highlight the differences in the spectral response of summer corn leaves with different level of nitrogen within “near infrared spectrum platform” and “green peak” at spinning stage. The wavelet-based PCs can manifest the changes in the spectra of summer corn leaves with different nitrogen levels. Trained GRNN model with wavelet-based PCs as inputs can predict leaf nitrogen content of summer corn. The model is reliable and practicable.

Abstract:Based on the monitored data of soil PH and measured VIS-NIR reflectance on given spots, the relationship between measured reflectance and soil PH was analyzed. Besides original field-measured spectrum (R), several spectral indices were also calculated: first derivative reflectance spectrum (FDR), inverse-log spectrum (lg(1/R)) and band depth (BD). Multivariate linear regression models were built to evaluate soil alkalinization level based on these four spectral indices and the model accuracy of PH fitting was discussed with validated sample group. The results showed that there is a significant positive correlation between soil PH and original reflectance. The accuracy of the model based on original spectrum(R) is the best with a value of R2 as high as 0.873. Thus original spectrum(R) had potential ability of rapid and exact estimation of changes in the alkalinization soil. The model can help to further the analysis of the ability of detecting alkalinization with image reflectance because of the original spectrum (R) measured directly from field .The accuracy of inverse-log spectrum predicting model was slightly lower than the accuracy of original reflectance predicting model, so inverse-log spectrum calculating was of less help to improve the predicting efficiency. The R2 of first derivative reflectance spectrum (FDR) and band depth (BD) were 0.728 and 0.648, which were not ideal for the prediction of alkalinization.

Abstract:The currently used single-channel algorithms for land surface temperature (LST) retrieval are mainly proposed for sensors with limited scopes. The coverage of the infrared camera (IRS) onboard HJ-1B satellite is broad, and the view zenith angle of IRS channel 4 can reach 33. Therefore, the effects of view angle should be eliminated when retrieving LST with IRS4. Based on atmospheric radiative transfer simulation, this research explored a look-up table for view zenith angle (VZA)-coefficients of atmospheric functions and then proposed an improved single-channel algorithm for estimating LST from IRS4 images. According to the fact that the overpass time of HJ-1B and Terra are very close, the research investigated the possibility to integrate the water vapor provided by MODIS into the improved single-channel algorithm. In addition, this research proposed a practical routine to calculate the land surface emissivity of IRS4. Validation shows that the average absolute error of the improved algorithm is below 1.1K, which is about 0.1~0.7K lower than the algorithm without considering the view zenith angle. Application to the HJ-1B satellite imagery indicated that land surface temperatures retrieved with the improved algorithm are consistent with those provided by MODIS product.

Abstract:According to cloud phase discrimination theory of spaceborne polarization lidar, and use of the method of temperature threshold for spaceborne millimeter wave radar for reference, a cloud phase discrimination algorithm using CloudSat and CALIPSO Satellite data based on support vector machines (SVM) method was established. The training and testing data of samples used for establishing SVM model were mainly derived from CloudSat 2B-GEOPROF-LIDAR, CALIPSO level 2 1km cloud layer, and ECMWF auxiliary temperature data products. The discrimination result was compared with CloudSat cloud phase product retrieved by temperature threshold method, CALIPSO cloud phase product and other relevant data. The research results show that this cloud phase discrimination technique, e.g. SVM method with combined data of radar and lidar detection, has a superior accuracy and can provide better vertical distribution information of cloud phase.

Abstract:Ambiguity function (AF) modeling of radar signals is a powerful approach to feature extraction and recognition of radar emitters. An AF subspace based optimization framework is proposed to identify radar emitters by exploring unintentional modulation on pulse (UMOP) features. First, near-zero Doppler cuts of AF were extracted as a preliminary feature subset. Then, two kinds of cut-concatenation schemes were designed to construct two different pairs of feature vectors with complementary information respectively, which will facilitate the subsequent feature fusion via canonical correlation analysis (CCA) or discriminative canonical correlation analysis (DCCA). Theoretical analysis and experimental results show that the proposed algorithms not only alleviate the calculation problem in the existing AF based method, but also improve the recognition performance considerably, due to the successful information fusion and redundancy reduction conducted in the AF subset.

Abstract:For more effective image thresholding, a novel and simple method was proposed which based directly on the histogram of the image. According to the intuitive appearance of the histogram and the influence of peaks and valleys to final threshold, a new thresholding measurement is defined creatively. Accumulating mutual recognitions of all other histogram bins and combining some speeding-up strategies, the proposed measurement makes image thresholding more practicable and applicable. The number of segmentation is determined by the percentage of the final recognition value. As can be seen from the comparison with other methods in experiments, results of the proposed method looks better than other ones. Moreover, the objects are highlighted well in infrared image.

Abstract:A novel local feature descriptor, called Local Contourlet Binary Pattern (LCBP), was developed in this paper. LCBP provides a multiscale and multidirectional representation for images since it integrates multiscale geometric analysis and local binary pattern operators. With the quadtree structure of LCBP and simplicity of the model itself, the LCBP coefficients were modeled by a two-state HMT that is in accordance with the intra-band, inter-band and inter-directional distributions of LCBP coefficients. Based on the LCBP-HMT model, an object classification method was further proposed to extract parameters of the LCBP-HMT model as features and classify the query samples by comparing the Kullback-Liebler distance between features of the query samples and that of the prototype objects. Experimental results illustrate the superiority of the LCBP over traditional wavelet features and Gaussian density function model features of contourlet coefficients in terms of the discrimination performance.

Abstract:The tree-structured Markov Random Field (TS-MRF) model defined on a single spatial resolution, which is capable of expressing the hierarchical structure implied in the image to be segmented, fails to describe its non-stationary property. In order to solve this problem, a new image modeling method in Wavelet domain—WTS-MRF was proposed. In this model, a sequence of MRFs were hierarchically defined in the format of the classification tree structure. Each node was associated with a set of MRFs defined on different resolutions, wherein the correlation between neighbor MRFs with different resolutions was considered in the form of conditional probability. The child MRF was nested in the region of the parent one on the same resolution. Based on the WTS-MRF model, a supervised recursive segmentation algorithm was proposed. The classification hierarchical tree was manually set as the priori information, and the corresponding statistics for each leaf node were obtained by the training data on each resolution. The implementation of this algorithm was both on the inner-scale and inter-scale level. The inner-scale recursion was executed on the lowest resolution, where the MRF corresponding to each node was sequentially and recursively estimated by the ICM algorithm from the root to leaves. The inter-scale recursion was implemented on the next finer resolution, in which the estimation of MRFs was sequentially initialized by the direct projection from the next lower resolution and recursively refined by the ICM algorithm. The final segmentation was obtained when the MRFs were estimated on the primary resolution. Two experiments verify the validity of the proposed method in terms of both visual quality and quantitative indicators (e.g. overall accuracy and Kappa coefficient).