In this paper, an image encryption algorithm on the basis of cellular neural networks (CNN) and compressive sensing (CS) is proposed. Firstly, four CNN with hyper chaotic behavior is introduced to generate chaotic sequence. Then, the index of the sorted chaotic sequence is used to control the generation of measurement matrix in CS procedure. Moreover, Lissajous map is served to produce asymptotic deterministic random measurement matrix instead of the common random measurement matrix. In addition, the chaotic sequence is normalized to 8-bit integer to diffuse the result after applying CS operation on the plain image, and the image after compression and encryption is obtained. The simulation results and analysis verify the proposed algorithm owns good security and ideal performance.
{"title":"An Image Compression-Encryption Algorithm Based on Cellular Neural Network and Compressive Sensing","authors":"Jia-Wen Lin, Yuling Luo, Junxiu Liu, Jinjie Bi, Senhui Qiu, Mingcan Cen, Zhixian Liao","doi":"10.1109/ICIVC.2018.8492882","DOIUrl":"https://doi.org/10.1109/ICIVC.2018.8492882","url":null,"abstract":"In this paper, an image encryption algorithm on the basis of cellular neural networks (CNN) and compressive sensing (CS) is proposed. Firstly, four CNN with hyper chaotic behavior is introduced to generate chaotic sequence. Then, the index of the sorted chaotic sequence is used to control the generation of measurement matrix in CS procedure. Moreover, Lissajous map is served to produce asymptotic deterministic random measurement matrix instead of the common random measurement matrix. In addition, the chaotic sequence is normalized to 8-bit integer to diffuse the result after applying CS operation on the plain image, and the image after compression and encryption is obtained. The simulation results and analysis verify the proposed algorithm owns good security and ideal performance.","PeriodicalId":173981,"journal":{"name":"2018 IEEE 3rd International Conference on Image, Vision and Computing (ICIVC)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127174041","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-06-01DOI: 10.1109/ICIVC.2018.8492816
Yibo Sun, Yifeng Zhang
A novel angle quantization index modulation watermarking scheme based on block compressive sensing (BCS-AQIM) is proposed to embed robust and secure watermark. In this algorithm, sparse random matrices constructed by chaotic sequence are chosen as the measurement matrix and the measurement vector of host image is obtained by block compressive sensing. In each block, two optimal measurements are chosen to embed the watermark into their angle. Then, the watermarked image is recovered through reconstruction algorithm. The measurement matrix and the position of watermarked measurements are used as a key. The performance of BCS-AQIM under AWGN attacks and its security are analyzed and assessed by simulations. Experiment results demonstrate that the proposed method is robust to different types of attacks and outperforms common existing methods in terms of the robustness.
{"title":"Angle Quantization Index Modulation Based on Block Compressive Sensing for Robust and Secure Image Watermarking","authors":"Yibo Sun, Yifeng Zhang","doi":"10.1109/ICIVC.2018.8492816","DOIUrl":"https://doi.org/10.1109/ICIVC.2018.8492816","url":null,"abstract":"A novel angle quantization index modulation watermarking scheme based on block compressive sensing (BCS-AQIM) is proposed to embed robust and secure watermark. In this algorithm, sparse random matrices constructed by chaotic sequence are chosen as the measurement matrix and the measurement vector of host image is obtained by block compressive sensing. In each block, two optimal measurements are chosen to embed the watermark into their angle. Then, the watermarked image is recovered through reconstruction algorithm. The measurement matrix and the position of watermarked measurements are used as a key. The performance of BCS-AQIM under AWGN attacks and its security are analyzed and assessed by simulations. Experiment results demonstrate that the proposed method is robust to different types of attacks and outperforms common existing methods in terms of the robustness.","PeriodicalId":173981,"journal":{"name":"2018 IEEE 3rd International Conference on Image, Vision and Computing (ICIVC)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127206150","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Multi-join query optimization is an important technique for designing and implementing database manage system. It is a crucial factor that affects the capability of database. This paper proposes a new algorithm to solve the problem of multi-join query optimization based on parallel ant colony optimization. In this paper, details of the algorithm used to solve multi-join query optimization problem have been interpreted, including how to define heuristic information, how to implement local pheromone update and global pheromone update and how to design state transition rule. After repeated iteration, a reasonable solution is obtained. Compared with genetic algorithm, the simulation result indicates that parallel ant colony optimization is more effective and efficient.
{"title":"Database Query Optimization Based on Parallel Ant Colony Algorithm","authors":"Wenbo Zheng, Xin Jin, Fei Deng, Shaocong Mo, Yili Qu, Yuntao Yang, X. Li, Sijie Long, Chengfeng Zheng, Jingyi Liu, Zefeng Xie","doi":"10.1109/ICIVC.2018.8492789","DOIUrl":"https://doi.org/10.1109/ICIVC.2018.8492789","url":null,"abstract":"Multi-join query optimization is an important technique for designing and implementing database manage system. It is a crucial factor that affects the capability of database. This paper proposes a new algorithm to solve the problem of multi-join query optimization based on parallel ant colony optimization. In this paper, details of the algorithm used to solve multi-join query optimization problem have been interpreted, including how to define heuristic information, how to implement local pheromone update and global pheromone update and how to design state transition rule. After repeated iteration, a reasonable solution is obtained. Compared with genetic algorithm, the simulation result indicates that parallel ant colony optimization is more effective and efficient.","PeriodicalId":173981,"journal":{"name":"2018 IEEE 3rd International Conference on Image, Vision and Computing (ICIVC)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126812917","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-06-01DOI: 10.1109/ICIVC.2018.8492820
Lingling Li, Yuan Wu, Yi Yang, Lian Li, Binbin Wu
Lung cancer has a very low cure rate in the advanced stages, with effective early detection, the survival rate of lung cancer could be highly raised. Detection of lung cancer in the early stages plays a vital role for human health. Computed tomography (CT) images, which provide electronic densities of tissues, are widely applied in radiotherapy planning. The proposed system based on CT technology consists of several steps, such as image acquisition, preprocessing, feature extraction, and classification. In the preprocessing stage, RGB images are converted to grayscale images, the median filter and the Wiener filter are used to uproot noises, Otsu thresholding method is applied to convert CT images free from noise to binary images, and REGIONPROPS function is used to exact body region from binary images. In the feature extraction stage, features, like Contrast, Correlation, Energy, Homogeneity, are extracted through statistic method Gray Level Co-occurrence Matrix (GLCM). In the final stage, extracted features, together with Support Vector Machine (SVM) and Back Propagation NeuralNetwork (BPNN), are used to identify lung cancer from CT images. The performance of the proposed system shows satisfactory results of 96.32% accuracy on SVM and 83.07% accuracy on BPNN respectively.
{"title":"A New Strategy to Detect Lung Cancer on CT Images","authors":"Lingling Li, Yuan Wu, Yi Yang, Lian Li, Binbin Wu","doi":"10.1109/ICIVC.2018.8492820","DOIUrl":"https://doi.org/10.1109/ICIVC.2018.8492820","url":null,"abstract":"Lung cancer has a very low cure rate in the advanced stages, with effective early detection, the survival rate of lung cancer could be highly raised. Detection of lung cancer in the early stages plays a vital role for human health. Computed tomography (CT) images, which provide electronic densities of tissues, are widely applied in radiotherapy planning. The proposed system based on CT technology consists of several steps, such as image acquisition, preprocessing, feature extraction, and classification. In the preprocessing stage, RGB images are converted to grayscale images, the median filter and the Wiener filter are used to uproot noises, Otsu thresholding method is applied to convert CT images free from noise to binary images, and REGIONPROPS function is used to exact body region from binary images. In the feature extraction stage, features, like Contrast, Correlation, Energy, Homogeneity, are extracted through statistic method Gray Level Co-occurrence Matrix (GLCM). In the final stage, extracted features, together with Support Vector Machine (SVM) and Back Propagation NeuralNetwork (BPNN), are used to identify lung cancer from CT images. The performance of the proposed system shows satisfactory results of 96.32% accuracy on SVM and 83.07% accuracy on BPNN respectively.","PeriodicalId":173981,"journal":{"name":"2018 IEEE 3rd International Conference on Image, Vision and Computing (ICIVC)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128079444","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-06-01DOI: 10.1109/ICIVC.2018.8492786
Zhen Wang, Xiaojun Yang
In order to enable the optical flow to track larger and faster moving targets, pyramid Lucas-Kanade optical flow method is used to detect and track moving targets. First, detecting the corners which is easy to track, in order to improve the tracking accuracy, detected corners and then calculate the sub-pixel corner, and then the video in each frame of the image layered in the image pyramid to calculate the optical flow at the top corner, use the next pyramid as the starting point of the pyramid and repeat this process until the bottom pyramid image, which can overcome the Lucas-Kanade optical flow method cannot track faster and larger movements the shortcomings, to achieve the tracking of moving goals.
{"title":"Moving Target Detection and Tracking Based on Pyramid Lucas-Kanade Optical Flow","authors":"Zhen Wang, Xiaojun Yang","doi":"10.1109/ICIVC.2018.8492786","DOIUrl":"https://doi.org/10.1109/ICIVC.2018.8492786","url":null,"abstract":"In order to enable the optical flow to track larger and faster moving targets, pyramid Lucas-Kanade optical flow method is used to detect and track moving targets. First, detecting the corners which is easy to track, in order to improve the tracking accuracy, detected corners and then calculate the sub-pixel corner, and then the video in each frame of the image layered in the image pyramid to calculate the optical flow at the top corner, use the next pyramid as the starting point of the pyramid and repeat this process until the bottom pyramid image, which can overcome the Lucas-Kanade optical flow method cannot track faster and larger movements the shortcomings, to achieve the tracking of moving goals.","PeriodicalId":173981,"journal":{"name":"2018 IEEE 3rd International Conference on Image, Vision and Computing (ICIVC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128195614","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-06-01DOI: 10.1109/ICIVC.2018.8492734
Jian Wu, Ning Yu, Bo Zhou, Yuwen Duan
Measurement reports (MR) are files generated by User Equipment and ENODEB which indicate the channel quality and are important for LTE network optimization. However, it is hard to process MR files for algorithm studies quickly and easily. Based on the special structure of MR files, this paper presents and compares three MR parsing methods based on C# and expatiates detailed operations by giving examples in different working scenes. The result shows that using these methods can greatly speed up the verification work of network optimization algorithm and has a guiding significance for large-scale optimization job for one province or even for the whole country.
{"title":"Rapid Processing Methods of Measurement Reports in LTE Network","authors":"Jian Wu, Ning Yu, Bo Zhou, Yuwen Duan","doi":"10.1109/ICIVC.2018.8492734","DOIUrl":"https://doi.org/10.1109/ICIVC.2018.8492734","url":null,"abstract":"Measurement reports (MR) are files generated by User Equipment and ENODEB which indicate the channel quality and are important for LTE network optimization. However, it is hard to process MR files for algorithm studies quickly and easily. Based on the special structure of MR files, this paper presents and compares three MR parsing methods based on C# and expatiates detailed operations by giving examples in different working scenes. The result shows that using these methods can greatly speed up the verification work of network optimization algorithm and has a guiding significance for large-scale optimization job for one province or even for the whole country.","PeriodicalId":173981,"journal":{"name":"2018 IEEE 3rd International Conference on Image, Vision and Computing (ICIVC)","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126696351","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-06-01DOI: 10.1109/ICIVC.2018.8492868
Jinhua Liu
With the increasing demands of copyright protection, digital watermarking has been paid more and more attention. In the design of a watermarking method, the modeling of signal by a general parametric family of statistical distributions plays an important role in many image watermarking applications. In this paper, the probability density function of wavelet coefficients is modeled by the generalized Gaussian distribution (GGD), and the decision threshold is obtained by the Neyman-Pearson (NP) criterion. In the procedure of watermark embedding, the energy of image block is considered in the watermark embedding. Only those blocks whose energy exceeds a predetermined threshold are used to embed the watermark data. Its improved robustness is due to embedding in the significant wavelet coefficients based on the energy scheme and control of its strength factor from the variance of coefficient. Experimental results demonstrate that the effectiveness of the presented watermarking and its robustness against common image processing and some kinds of geometric attacks.
{"title":"An Image Watermarking Algorithm Based on Energy Scheme in the Wavelet Transform Domain","authors":"Jinhua Liu","doi":"10.1109/ICIVC.2018.8492868","DOIUrl":"https://doi.org/10.1109/ICIVC.2018.8492868","url":null,"abstract":"With the increasing demands of copyright protection, digital watermarking has been paid more and more attention. In the design of a watermarking method, the modeling of signal by a general parametric family of statistical distributions plays an important role in many image watermarking applications. In this paper, the probability density function of wavelet coefficients is modeled by the generalized Gaussian distribution (GGD), and the decision threshold is obtained by the Neyman-Pearson (NP) criterion. In the procedure of watermark embedding, the energy of image block is considered in the watermark embedding. Only those blocks whose energy exceeds a predetermined threshold are used to embed the watermark data. Its improved robustness is due to embedding in the significant wavelet coefficients based on the energy scheme and control of its strength factor from the variance of coefficient. Experimental results demonstrate that the effectiveness of the presented watermarking and its robustness against common image processing and some kinds of geometric attacks.","PeriodicalId":173981,"journal":{"name":"2018 IEEE 3rd International Conference on Image, Vision and Computing (ICIVC)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123673710","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-06-01DOI: 10.1109/ICIVC.2018.8492778
Cui Zhou, Jinghong Zhou
The obtained precisely high frequency information is the key of single-frame image super-resolution reconstruction by using two-dimensional wavelet. Because the bicubic interpolation of high frequency components decomposed by wavelet will introduce noise, it will affect reconstruction effect. An improved algorithm using Fourier transform and zero-padding resampling instead of bicubic interpolation is proposed in this paper. The advantage of frequency domain interpolation is obtained by using Fourier transform and zero-padding resampling. And high frequency components obtained by wavelet decomposition of the original image can be interpolated optimally without introducing noise, which makes the high frequency details more precise in the reconstruction process. The experimental results show that the improved algorithm is superior to the traditional two-dimensional wavelet reconstruction algorithm, which can be applied to the single-frame remote sensing image super-resolution reconstruction.
{"title":"Single-Frame Remote Sensing Image Super-Resolution Reconstruction Algorithm Based on Two-Dimensional Wavelet","authors":"Cui Zhou, Jinghong Zhou","doi":"10.1109/ICIVC.2018.8492778","DOIUrl":"https://doi.org/10.1109/ICIVC.2018.8492778","url":null,"abstract":"The obtained precisely high frequency information is the key of single-frame image super-resolution reconstruction by using two-dimensional wavelet. Because the bicubic interpolation of high frequency components decomposed by wavelet will introduce noise, it will affect reconstruction effect. An improved algorithm using Fourier transform and zero-padding resampling instead of bicubic interpolation is proposed in this paper. The advantage of frequency domain interpolation is obtained by using Fourier transform and zero-padding resampling. And high frequency components obtained by wavelet decomposition of the original image can be interpolated optimally without introducing noise, which makes the high frequency details more precise in the reconstruction process. The experimental results show that the improved algorithm is superior to the traditional two-dimensional wavelet reconstruction algorithm, which can be applied to the single-frame remote sensing image super-resolution reconstruction.","PeriodicalId":173981,"journal":{"name":"2018 IEEE 3rd International Conference on Image, Vision and Computing (ICIVC)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121844178","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-06-01DOI: 10.1109/ICIVC.2018.8492761
Yuanyuan Gao, Guoliang Liu, Chao Ma
Image de-hazing is important for many computer vision applications. However, dense haze removal from a single image remains to be a challenging problem. Key insight that limits the performance of existing de-hazing algorithms is that these algorithms utilize the classic haze imaging model, which is based on an assumption that radiation on the object surface is sufficient and white. However, in dense hazy conditions, this hypothesis is easily broken. Thus, removing dense haze using classic de-hazing algorithms would result in dark-look or color shift. Therefore, in this paper, we propose a dense hazy image enhancement algorithm based on the generalized haze imaging model. The proposed algorithm includes two steps: Frist, we estimate pseudo ambient illumination and remove it to obtain an illumination balanced result. Second, we calculate the scene reflectivity as the enhanced result based on the spherical coordinate system. Experimental results demonstrate that the proposed algorithm surpasses state-of-the-art algorithms in most cases.
{"title":"Dense Hazy Image Enhancement Based on Generalized Imaging Model","authors":"Yuanyuan Gao, Guoliang Liu, Chao Ma","doi":"10.1109/ICIVC.2018.8492761","DOIUrl":"https://doi.org/10.1109/ICIVC.2018.8492761","url":null,"abstract":"Image de-hazing is important for many computer vision applications. However, dense haze removal from a single image remains to be a challenging problem. Key insight that limits the performance of existing de-hazing algorithms is that these algorithms utilize the classic haze imaging model, which is based on an assumption that radiation on the object surface is sufficient and white. However, in dense hazy conditions, this hypothesis is easily broken. Thus, removing dense haze using classic de-hazing algorithms would result in dark-look or color shift. Therefore, in this paper, we propose a dense hazy image enhancement algorithm based on the generalized haze imaging model. The proposed algorithm includes two steps: Frist, we estimate pseudo ambient illumination and remove it to obtain an illumination balanced result. Second, we calculate the scene reflectivity as the enhanced result based on the spherical coordinate system. Experimental results demonstrate that the proposed algorithm surpasses state-of-the-art algorithms in most cases.","PeriodicalId":173981,"journal":{"name":"2018 IEEE 3rd International Conference on Image, Vision and Computing (ICIVC)","volume":"104 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122675995","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-06-01DOI: 10.1109/ICIVC.2018.8492811
Zheng Mingyue, Su Jian, Ge Jianyun
In order to meet the needs for the integration and miniaturization of CCD imaging circuit, a software integrated design method is provided in this paper. Using FPGA as the core of the imaging circuit, the three parts of the traditional CCD imaging circuit, which is focal plane software, signal processing software and integration timing software, are integrated into a piece of FPGA, mainly generating the timing drive signal needed for CCD imaging, configuring the A/D converter to realize analog to digital conversion, coding and synthesizing the converted image data and arranging the data transmission format, realizing the communication between the imaging circuit and the outside by the telemetry and telecontrol three wire interface, so as to receive the auxiliary data on the satellite and the adjustment instructions of the imaging parameters. The experimental results show that the integrated software design of this paper can realize all functions of focal plane software, signal processing software and integration timing software. The imaging effect is clear, the hardware circuit is simplified and the software integration is improved, and it has high engineering application value.
{"title":"Integrated Design of Software for CCD Imaging Circuit Based on FPGA","authors":"Zheng Mingyue, Su Jian, Ge Jianyun","doi":"10.1109/ICIVC.2018.8492811","DOIUrl":"https://doi.org/10.1109/ICIVC.2018.8492811","url":null,"abstract":"In order to meet the needs for the integration and miniaturization of CCD imaging circuit, a software integrated design method is provided in this paper. Using FPGA as the core of the imaging circuit, the three parts of the traditional CCD imaging circuit, which is focal plane software, signal processing software and integration timing software, are integrated into a piece of FPGA, mainly generating the timing drive signal needed for CCD imaging, configuring the A/D converter to realize analog to digital conversion, coding and synthesizing the converted image data and arranging the data transmission format, realizing the communication between the imaging circuit and the outside by the telemetry and telecontrol three wire interface, so as to receive the auxiliary data on the satellite and the adjustment instructions of the imaging parameters. The experimental results show that the integrated software design of this paper can realize all functions of focal plane software, signal processing software and integration timing software. The imaging effect is clear, the hardware circuit is simplified and the software integration is improved, and it has high engineering application value.","PeriodicalId":173981,"journal":{"name":"2018 IEEE 3rd International Conference on Image, Vision and Computing (ICIVC)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124968334","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：