Abstract： Based on digital signal processor（DSP） and field programmable gate array（FPGA） techniques, the architecture of super large view field（SLVF） panoramic night vision image processing hardware platform wa...Abstract： Based on digital signal processor（DSP） and field programmable gate array（FPGA） techniques, the architecture of super large view field（SLVF） panoramic night vision image processing hardware platform was established. The panoramic unwrapping and correcting algorithm, up to a full 360°, based on coordinate rotation digital computer （CORDIC） and night vision image enhancement algorithm, based on histogram equalization theory and edge detection theory, was presented in this paper, with the purpose of processing night vision dynamic panoramic annular image. The annular image can be unwrapped and corrected to conventional rectangular panorama by the panoramic image processing algorithm, which uses the pipelined CORDIC configuration to realize a trigonometric function generator with high speed and high precision. Histogram equalization algorithm can perfectly enhance the contrast of the night vision image. Edge detection algorithm can be propitious to find and detect small dim dynamic targets in night vision circumstances. After abundant experiment, the al- gorithm for panoramic image processing and night vision image enhancement is successfully implemented in FPGA and DSP. The panoramic night vision image system is a compact device, with no external rotating parts. And the system can reliably and dynamically detect 360＊ SLVF panoramic night vision image.展开更多
In mausoleum murals, existing bubbles are one kind of the most harmful defects for the repair and protection of relics. For this reason, it is necessary to detect bubbles, especially the ones with small size. A method...In mausoleum murals, existing bubbles are one kind of the most harmful defects for the repair and protection of relics. For this reason, it is necessary to detect bubbles, especially the ones with small size. A method to detect the small bubbles with enhanced terahertz （THz） images is proposed. To simulate the bubbles in the mausoleum murals, circular grooves have been hidden in the plaster and then measured by the THz reflected time domain spectroscopy imaging system. To observe the small bubbles in murals, a comprehensive enhancement algorithm is adopted to process the obtained THz images. With the enhanced method, the circular grooves in the murals can be observed clearly, even for the circular groove with a diameter of 1.5 mm. The results indicate that the proposed comprehensive method can be used to detect the tiny defects of murals.展开更多
To overcome the limitations of conventional speech enhancement methods, such as inaccurate voice activity detector(VAD) and noise estimation, a novel speech enhancement algorithm based on the approximate message passi...To overcome the limitations of conventional speech enhancement methods, such as inaccurate voice activity detector(VAD) and noise estimation, a novel speech enhancement algorithm based on the approximate message passing(AMP) is adopted. AMP exploits the difference between speech and noise sparsity to remove or mute the noise from the corrupted speech. The AMP algorithm is adopted to reconstruct the clean speech efficiently for speech enhancement. More specifically, the prior probability distribution of speech sparsity coefficient is characterized by Gaussian-model, and the hyper-parameters of the prior model are excellently learned by expectation maximization(EM) algorithm. We utilize the k-nearest neighbor(k-NN) algorithm to learn the sparsity with the fact that the speech coefficients between adjacent frames are correlated. In addition, computational simulations are used to validate the proposed algorithm, which achieves better speech enhancement performance than other four baseline methods-Wiener filtering, subspace pursuit(SP), distributed sparsity adaptive matching pursuit(DSAMP), and expectation-maximization Gaussian-model approximate message passing(EM-GAMP) under different compression ratios and a wide range of signal to noise ratios(SNRs).展开更多
针对强日光环境下OCC(Optical Camera Communication)系统接收端解码困难的问题,提出了基于分段式线性灰度变换的Gradient-Harris解码算法。首先搭建一套OCC实验系统,接收端相机采集原始图像,利用标准相关系数匹配方法提取目标LED阵列...针对强日光环境下OCC(Optical Camera Communication)系统接收端解码困难的问题,提出了基于分段式线性灰度变换的Gradient-Harris解码算法。首先搭建一套OCC实验系统,接收端相机采集原始图像,利用标准相关系数匹配方法提取目标LED阵列区域。其次通过分段式线性灰度变换对目标LED阵列区域进行图像增强,利用Gradient-Harris解码算法进行目标LED阵列的形状提取和状态识别。实验结果表明,应用基于分段式线性灰度变换的Gradient-Harris解码算法,强日光环境下OCC实验系统的平均解码速率为128.08 bit/s,平均误码率为4.38×10^(-4),最大通信距离为55 m。展开更多
文摘Abstract： Based on digital signal processor（DSP） and field programmable gate array（FPGA） techniques, the architecture of super large view field（SLVF） panoramic night vision image processing hardware platform was established. The panoramic unwrapping and correcting algorithm, up to a full 360°, based on coordinate rotation digital computer （CORDIC） and night vision image enhancement algorithm, based on histogram equalization theory and edge detection theory, was presented in this paper, with the purpose of processing night vision dynamic panoramic annular image. The annular image can be unwrapped and corrected to conventional rectangular panorama by the panoramic image processing algorithm, which uses the pipelined CORDIC configuration to realize a trigonometric function generator with high speed and high precision. Histogram equalization algorithm can perfectly enhance the contrast of the night vision image. Edge detection algorithm can be propitious to find and detect small dim dynamic targets in night vision circumstances. After abundant experiment, the al- gorithm for panoramic image processing and night vision image enhancement is successfully implemented in FPGA and DSP. The panoramic night vision image system is a compact device, with no external rotating parts. And the system can reliably and dynamically detect 360＊ SLVF panoramic night vision image.
基金supported by the 973 Program of China under Grant No.2013CBA01702National Natural Science Foundation of China under Grant No.11474206,No.91233202,No.11374216,and No.11404224+3 种基金Program for New Century Excellent Talents in University under Grant No.NCET-12-0607Scientific Research Project of Beijing Education Commission under Grant No.KM201310028005Specialized Research Fund for the Doctoral Program of Higher Education under Grant No.20121108120009the Beijing Youth Top-Notch Talent Training Plan under Grant No.CIT&TCD201504080
文摘In mausoleum murals, existing bubbles are one kind of the most harmful defects for the repair and protection of relics. For this reason, it is necessary to detect bubbles, especially the ones with small size. A method to detect the small bubbles with enhanced terahertz （THz） images is proposed. To simulate the bubbles in the mausoleum murals, circular grooves have been hidden in the plaster and then measured by the THz reflected time domain spectroscopy imaging system. To observe the small bubbles in murals, a comprehensive enhancement algorithm is adopted to process the obtained THz images. With the enhanced method, the circular grooves in the murals can be observed clearly, even for the circular groove with a diameter of 1.5 mm. The results indicate that the proposed comprehensive method can be used to detect the tiny defects of murals.
基金supported by National Natural Science Foundation of China(NSFC)(No.61671075)Major Program of National Natural Science Foundation of China(No.61631003)。
文摘To overcome the limitations of conventional speech enhancement methods, such as inaccurate voice activity detector(VAD) and noise estimation, a novel speech enhancement algorithm based on the approximate message passing(AMP) is adopted. AMP exploits the difference between speech and noise sparsity to remove or mute the noise from the corrupted speech. The AMP algorithm is adopted to reconstruct the clean speech efficiently for speech enhancement. More specifically, the prior probability distribution of speech sparsity coefficient is characterized by Gaussian-model, and the hyper-parameters of the prior model are excellently learned by expectation maximization(EM) algorithm. We utilize the k-nearest neighbor(k-NN) algorithm to learn the sparsity with the fact that the speech coefficients between adjacent frames are correlated. In addition, computational simulations are used to validate the proposed algorithm, which achieves better speech enhancement performance than other four baseline methods-Wiener filtering, subspace pursuit(SP), distributed sparsity adaptive matching pursuit(DSAMP), and expectation-maximization Gaussian-model approximate message passing(EM-GAMP) under different compression ratios and a wide range of signal to noise ratios(SNRs).
文摘针对强日光环境下OCC(Optical Camera Communication)系统接收端解码困难的问题,提出了基于分段式线性灰度变换的Gradient-Harris解码算法。首先搭建一套OCC实验系统,接收端相机采集原始图像,利用标准相关系数匹配方法提取目标LED阵列区域。其次通过分段式线性灰度变换对目标LED阵列区域进行图像增强,利用Gradient-Harris解码算法进行目标LED阵列的形状提取和状态识别。实验结果表明,应用基于分段式线性灰度变换的Gradient-Harris解码算法,强日光环境下OCC实验系统的平均解码速率为128.08 bit/s,平均误码率为4.38×10^(-4),最大通信距离为55 m。
