National Key Laboratory of Science and Technology on Multispectral Information Processing

Wuhan, China

National Key Laboratory of Science and Technology on Multispectral Information Processing

Wuhan, China
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Peng S.,National Key Laboratory of Science and Technology on Multispectral Information Processing | Peng S.,Huazhong University of Science and Technology | Yuan Y.,National Key Laboratory of Science and Technology on Multispectral Information Processing | Yuan Y.,Huazhong University of Science and Technology | And 6 more authors.
Optics InfoBase Conference Papers | Year: 2016

The current studies indicate that surface plasmons (SP) stimulated by metallic nanostructures can break the diffraction limit and concentrate light into sub-wavelength scale, which provide a method to study the interaction between near-field optics and metal nanoparticles. A kind of periodically patterned metallic nanostructures that combine nanometer thickness gold film with silicon wafer has been developed in this paper. Through changing the structural parameters and further comparing the reflectance and electric field intensity distribution based on simulation, the most effective nanostructures can be selected. The experimental results demonstrate that the metallic nanostructures can effectively stimulate surface plasmons. Moreover, petal-shaped field enhancement have been observed on scattering near-field optical microscope SNOM images of λ =633nm, which are prove to be formed by the propagation of surface plasmons. © OSA 2016.


Bai X.D.,Huazhong University of Science and Technology | Bai X.D.,National Key Laboratory of Science and Technology on Multispectral Information Processing | Cao Z.G.,Huazhong University of Science and Technology | Cao Z.G.,National Key Laboratory of Science and Technology on Multispectral Information Processing | And 4 more authors.
Computers and Electronics in Agriculture | Year: 2013

Crop segmentation from the images taken in the outdoor fields is a complex task. In this paper, a new morphology modeling method is utilized to establish the crop color model in the CIE L*a*b* (or Lab for simplification) color space and to realize the crop image segmentation. In the supervised learning stage, morphology modeling is applied to deal with the color characteristics of the crop with respect to the pixel lightness component and establish the crop color model. To verify the performance of the proposed method, 56 test images which in size of 601×601 and taken from April 27, 2011 to May 21, 2011 are utilized to compare the proposed method with eight other famous approaches. Experiment shows that the segmentation quality of the proposed method is approximately 87.2% for the Automatic Target Recognition Working Group (ATRWG) evaluation method and 96.0% for another evaluation method. Moreover, the segmentation performance for images taken on cloudy, overcast and sunny days is analyzed. Experiment demonstrates that our method is robust to the variation of illumination in the field and performed better than eight other approaches. Furthermore, the impact of different structuring element types to the proposed method is compared. Overall, the proposed crop segmentation method can be used to crop segmentation in the field effectively. © 2013 Elsevier B.V.


Yu Z.,Huazhong University of Science and Technology | Yu Z.,National Key Laboratory of Science and Technology on Multispectral Information Processing | Cao Z.,Huazhong University of Science and Technology | Cao Z.,National Key Laboratory of Science and Technology on Multispectral Information Processing | And 10 more authors.
Agricultural and Forest Meteorology | Year: 2013

Growth stage information of field crops is not only an important basic data for analyzing the relationship between the crop growth process and the agrometeorological conditions, but it is also useful for various aspects of precision agriculture. Up to now, it is primarily obtained manually, which is time-consuming, labor-intensive, subjective and discontinuous. Therefore, a noninvasive method to note observations that also proves to be more efficient, continuous, and automatic is needed. At present, an alternative method based on computer vision has been widely used for monitoring crop growth status due to advantages linked to its low-cost, its intuitiveness and non-contact manner of data gathering it provides. However, little research has been done to improve close observation of different growth stages of field crops using digital cameras. To overcome the drawbacks caused by the current manual observation, a study was conducted to explore the application of computer vision technology for the automatic detection technology of two critical growth stages of maize (emergence and three-leaf stage). In order to identify the growth stages, the first task is to extract the plants from images properly. According to complex factors on farm fields, we proposed a novel crops segmentation method (AP-HI) which is robust and not sensitive to the challenging variation of outdoor luminosity and complex environmental elements. It has laid the foundation for subsequent studies. By virtue of the AP-HI, two automatic detection methods based on imaging were investigated for the two critical growth stages of maize. The former method uses the spatial distribution feature to judge accurately whether the field crop has reached the emergence stage or not. The latter uses the skeleton endpoint to characterize the leaf of seedling and transforms a matter of judgment into that of probability estimation, which leads to the final conclusion. In order to verify the feasibility and validity of our proposed methods, the comparing experiments have been carried out. Five well-established algorithms were utilized to make comparison with AP-HI and its results showed that our method outperformed the other algorithms in yielding the highest performance of 96.68% with the lowest standard deviation of 2.37%. As for the two automatic detection methods, the crops of two experimental fields located in Zhengzhou, Henan and Taian, Shandong provinces in China were observed both with a human observer and by using automated routines to process images obtained from a camera. In determining the time at which a growth stage occurred, the proposed methods produced the similar results to the manual observation method. Overall, the automated methods can meet the demand for practical observation needed for agronomic modeling and in triggering action alerts to farmers. © 2013 Elsevier B.V.


Tong Q.,National Key Laboratory of Science and Technology on Multispectral Information Processing | Lei Y.,National Key Laboratory of Science and Technology on Multispectral Information Processing | Zhang X.,Huazhong University of Science and Technology
Proceedings of SPIE - The International Society for Optical Engineering | Year: 2015

As we all know, because the index of refraction of the conventional microlens array (MLA) is not variable, the wavefront sensor based on the conventional MLA can only obtain the intensity image with low-resolution when it is used to measure the wavefront information simultaneously. In this paper, we use the dual-mode photosensitive arrays based on the liquid crystal (LC) MLA and CMOS sensors to obtain both intensity images with high-resolution and wavefronts. The dual-mode photosensitive arrays can work between an imaging mode and a wavefront sensor mode by switching the voltage off and on. In the experiment, we compare the composite wavefront of the object exposured in a white light with the wavefronts of the same object in tricolor laser. Because using the monochromatic light to measure the wavefront of an object may loss some information, it is a better method to use the white light for obtaining the wavefront information of the single object in the black background. We also discussed how to mix the wavefronts of the red green and blue laser to make the mixed wavefront which is closer to the composite wavefront. © 2015 SPIE.


Zhang H.,National Key Laboratory of Science and Technology on Multispectral Information Processing | Zhang H.,Huazhong University of Science and Technology | Muhammmad A.,Huazhong University of Science and Technology | Luo J.,National Key Laboratory of Science and Technology on Multispectral Information Processing | And 11 more authors.
Applied Optics | Year: 2014

An electrically tunable infrared (IR) filter based on the liquid crystal (LC) Fabry - Perot (FP) key structure, which works in the wavelength range from 5.5 to 12 μm, is designed and fabricated successfully. Both planar reflective mirrors with a very high reflectivity of ∼95%, which are shaped by depositing a layer of aluminum (Al) film over one side of a double-sided polished zinc selenide wafer, are coupled into a dual-mirror FP cavity. The LC materials are filled into the FP cavity with a thickness of ∼7.5 μm for constructing the LC - FP filter, which is a typical type of sandwich architecture. The top and bottom mirrors of the FP cavity are further coated by an alignment layer with a thickness of ∼100 nm over Al film. The formed alignment layer is rubbed strongly to shape relatively deep V-grooves to anchor LC molecules effectively. Common optical tests show some particular properties; for instance, the existing three transmission peaks in the measured wavelength range, the minimum full width at half-maximum being ∼120 nm, and the maximum adjustment extent of the imaging wavelength being ∼500 nm through applying the voltage driving signal with a root mean square (RMS) value ranging from 0 to ∼19.8 V. The experiment results are consistent with the simulation, according to our model setup. The spectral images obtained in the long-wavelength IR range, through the LC - FP device driven by the voltage signal with a different RMS value, demonstrates the prospect of the realization of smart spectral imaging and further integrating the LC - FP filter with IR focal plane arrays. The developed LC - FP filters show some advantages, such as electrically tunable imaging wavelength, very high structural and photoelectronic response stability, small size and low power consumption, and a very high filling factor of more than 95% compared with common MEMS-FP spectral imaging approaches. © 2014 Optical Society of America.


Tong Q.,National Key Laboratory of Science and Technology on Multispectral Information Processing | Tong Q.,Huazhong University of Science and Technology | Zhang X.,National Key Laboratory of Science and Technology on Multispectral Information Processing | Zhang X.,Huazhong University of Science and Technology | And 3 more authors.
Proceedings of SPIE - The International Society for Optical Engineering | Year: 2013

The liquid crystal (LC) device with the circle aperture electrode can be used as a convex lens. The index of refraction of the LC lens can be easily changed by the voltage signal; the arrayed LC lens can be used in the imaging sensors. Comparing with the traditional optical lens, the LC lens has a more effective architecture. In this paper, we present an imaging sensor with a new type LC structure composed of three layers of top electrodes and a joint bottom electrode, and simulating the tunable spatial resolution architecture carried out by applying voltage signal over different ITO electrode in LC lenses coupled with arrayed imaging sensors. From the result of the simulation, we can find that changing the spatial resolution by our architecture can be achieved. © 2013 SPIE.


Ye M.,Huazhong University of Science and Technology | Ye M.,National Key Laboratory of Science and Technology on Multispectral Information Processing | Cao Z.,Huazhong University of Science and Technology | Cao Z.,National Key Laboratory of Science and Technology on Multispectral Information Processing | And 4 more authors.
Computers and Electronics in Agriculture | Year: 2015

In the process of agriculture automation, mechanization and intelligentialization, image segmentation for crop extraction plays a crucial role. However, the performance of crop segmentation is closely related to the quality of the captured image, which is easily affected by the variability, randomness, and complexity of the natural illumination. The previously proposed crop extraction approaches produce inaccurate segmentation under natural illumination when highlight occurs. And specularity removal techniques are still hard to improve the crop extraction performance, because of the flaw of their assumption and the high requirement of the experimental configuration. In this paper, we propose a novel crop extraction method resistant to the strong illumination by using probabilistic superpixel Markov random field. Our method is based on the assumption that color changes gradually between highlight areas and its neighboring non-highlight areas and the same holds true for the other regions. This priori knowledge is embedded into the MRF-MAP framework by modeling the local and mutual evidences of nodes. Besides, superpixel and Fisher linear discriminant are utilized to construct the probabilistic superpixel patches. Loopy belief propagation algorithm is adopted in the optimization step. And the label for the crop segmentation is provided in the final iteration result. We also compare our method to the other state-of-the-art approaches. The results demonstrate that our method is resistant to the strong illumination and can be applied to generic species. Moreover, our approach is also capable of extracting the crop from the shadow regions. Statistics from comparative experiments manifest that our crop segmentation method yields the highest mean value of 92.29% with the lowest standard deviation of 4.65%, which can meet the requirement of practical uses in our agriculture automatic vision system. © 2015 Elsevier B.V.


Lan X.-J.,National Key Laboratory of Science and Technology on Multispectral Information Processing | Lan X.-J.,Huazhong University of Science and Technology | Liu L.,National Key Laboratory of Science and Technology on Multispectral Information Processing | Liu L.,Huazhong University of Science and Technology | And 2 more authors.
Acta Astronautica | Year: 2016

A guidance scheme has been proposed based on a new online trajectory planning algorithm for an unpowered reusable launch vehicle (RLV) in the terminal area energy management (TAEM) phase. The trajectory planning algorithm is able to rapidly generate a feasible path from the current state to a desired state at approach and landing interface (ALI) based on the dynamic pressure profile and new ground track geometry. Simple guidance laws are used to keep the RLV flying along the reference path which can be adjusted online by five related parameters. Then, the effectiveness and adaptability of the proposed TAEM guidance scheme is demonstrated by numerical trials with variations in the initial energy, position and aerodynamic performance. © 2015 IAA. Published by Elsevier Ltd. All rights reserved.


Chen Z.,Huazhong University of Science and Technology | Chen Z.,National Key Laboratory of Science and Technology on Multispectral Information Processing | Fang H.,Huazhong University of Science and Technology | Fang H.,National Key Laboratory of Science and Technology on Multispectral Information Processing | And 2 more authors.
IEEE Transactions on Industrial Electronics | Year: 2016

Well-established theory of subspace system identification and model-based fault detection and isolation (FDI) enable the birth of subspace-based data-driven FDI approach. In this paper, we develop subspace-based FDI approach with a scheme of weighted historical and operating data. We propose two kinds of weighted data-driven fault detection algorithms and present fault isolation algorithm and its modified version incorporated with forgetting factors. Analysis of sensitivity and precision shows the weighted algorithms can obtain more accurate results without loss of sensitivity. Effectiveness and improvements of the proposed algorithms are validated on the widely used benchmark platform of Tennessee-Eastman process (TEP). © 1982-2012 IEEE.


Yang X.,National Key Laboratory of Science and Technology on Multispectral Information Processing | Zhong S.,Huazhong University of Science and Technology
Proceedings - 2015 Chinese Automation Congress, CAC 2015 | Year: 2015

Dynamic target tracking technology has been widely used in airborne fire control systems, airborne warning systems, onboard systems and battlefield surveillance target tracking. The dynamic target tracking technology is used in automatic target detection, identification and positioning to control the movement of the camera. High-sensitivity CCD camera system is widely used in Modern high-speed camera. When the camera is used in the scene that target is too bright and ground is in large variation, the images are easily saturated. The gray of collected images is directly related to the amount of light enter the camera, so the image gray relies on the adjustment of light amount through an optical system. The means of the exposure control focuses on the adjustment of image brightness, and the amount of light through an optical system relies on the integration time to adjust the brightness of the images, in our system, we adjust the integration time to change the image gray. We propose a method for automatically adjusting the gray of image, which takes the image gray as the feedback signal of FID system to adjust the camera's exposure time. So we can get stable and desirable image gray under high image frame rate in restricted time. In different environment with different illumination, this technology is mainly used in adjusting the image gray to an appropriate value. Furthermore, the tracking camera attaches importance not only on the dimming range but also on the dimming speed. Our algorithm can guarantee a quick adjustment and get a stable and desired image gray. © 2015 IEEE.

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