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RISS 인기검색어
- 검색키워드
- 저자 : HeXiong Liu (검색결과 4 건)
- 무료
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- 유료
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A Spectral-spatial Cooperative Noise-evaluation Method for Hyperspectral Imaging
Bing Zhou,Bingxuan Li,Xuan He,Hexiong Liu 한국광학회 2020 Current Optics and Photonics Vol.4 No.6
Hyperspectral images feature a relatively narrow band and are easily disturbed by noise. Accurate estimation of the types and parameters of noise in hyperspectral images can provide prior knowledge for subsequent image processing. Existing hyperspectral-noise estimation methods often pay more attention to the use of spectral information while ignoring the spatial information of hyperspectral images. To evaluate the noise in hyperspectral images more accurately, we have proposed a spectral-spatial cooperative noiseevaluation method. First, the feature of spatial information was extracted by Gabor-filter and K-means algorithms. Then, texture edges were extracted by the Otsu threshold algorithm, and homogeneous image blocks were automatically separated. After that, signal and noise values for each pixel in homogeneous blocks were split with a multiple-linear-regression model. By experiments with both simulated and real hyperspectral images, the proposed method was demonstrated to be effective and accurate, and the composition of the hyperspectral image was verified.
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Laser-induced Damage to Polysilicon Microbridge Component
Bing Zhou,Xuan He,Bingxuan Li,HeXiong Liu,Kaifei Peng 한국광학회 2019 Current Optics and Photonics Vol.3 No.6
Based on the typical pixel structure and parameters of a polysilicon uncooled bolometer, the absorption rate of a polysilicon microbridge infrared detector for 10.6 µm laser energy was calculated through the optical admittance method, and the thermal coupling model of a polysilicon microbridge component irradiated by far infrared laser was established based on theoretical formulas. Then a numerical simulation study was carried out by means of finite element analysis for the actual working environment. It was found that the maximum temperature and maximum stress of the microbridge component are approximately exponentially changing with the laser power of the irradiation respectively and that they increase monotonically. The highest temperature zone of the model is gradually spread by the two corners of the bridge surface that are not connected to the bridge legs, and the maximum stress acts on both sides of the junction of the microbridge legs and the substrate. The mechanism of laser-induced hard damage to polysilicon detectors is the melting damage caused by high temperature. This paper lays the foundation for the subsequent study of the interference mechanism of the laser on working state polysilicon detectors.
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Adaptive Hyperspectral Image Classification Method Based on Spectral Scale Optimization
Bing Zhou,Li Bingxuan,Xuan He,HeXiong Liu 한국광학회 2021 Current Optics and Photonics Vol.5 No.3
The adaptive sparse representation (ASR) can effectively combine the structure information of a sample dictionary and the sparsity of coding coefficients. This algorithm can effectively consider the correlation between training samples and convert between sparse representation-based classifier (SRC) and collaborative representation classification (CRC) under different training samples. Unlike SRC and CRC which use fixed norm constraints, ASR can adaptively adjust the constraints based on the correlation between different training samples, seeking a balance between l 1 and l 2 norm, greatly strengthening the robustness and adaptability of the classification algorithm. The correlation coefficients (CC) can better identify the pixels with strong correlation. Therefore, this article proposes a hyperspectral image classification method called correlation coefficients and adaptive sparse representation (CCASR), based on ASR and CC. This method is divided into three steps. In the first step, we determine the pixel to be measured and calculate the CC value between the pixel to be tested and various training samples. Then we represent the pixel using ASR and calculate the reconstruction error corresponding to each category. Finally, the target pixels are classified according to the reconstruction error and the CC value. In this article, a new hyperspectral image classification method is proposed by fusing CC and ASR. The method in this paper is verified through two sets of experimental data. In the hyperspectral image (Indian Pines), the overall accuracy of CCASR has reached 0.9596. In the hyperspectral images taken by HIS-300, the classification results show that the classification accuracy of the proposed method achieves 0.9354, which is better than other commonly used methods.
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Joint-transform Correlator Multiple-image Encryption System Based on Quick-response Code Key
Qi Chen,Xueju Shen,Yue Cheng,Fuyu Huang,Chao Lin,HeXiong Liu 한국광학회 2019 Current Optics and Photonics Vol.3 No.4
A method for joint-transform correlator (JTC) multiple-image encryption based on a quick-response (QR) code key is proposed. The QR codes converted from different texts are used as key masks to encrypt and decrypt multiple images. Not only can Chinese text and English text be used as key text, but also symbols can be used. With this method, users have no need to transmit the whole key mask; they only need to transmit the text that is used to generate the key. The correlation coefficient is introduced to evaluate the decryption performance of our proposed cryptosystem, and we explore the sensitivity of the key mask and the capability for multiple-image encryption. Robustness analysis is also conducted in this paper. Computer simulations and experimental results verify the correctness of this method.
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