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	Effect of the number of projections in X-ray CT imaging on image quality and digital volume correlation measurement 期刊论文 OAI收割 MEASUREMENT, 2022, 卷号: 194, 页码: 12 作者: Zhang, Xuanhao; Sun, Lijuan; Wang, Bo; Pan, Bing; Sun LJ(孙立娟) \| 收藏 \| 浏览/下载：33/0 \| 提交时间：2022/07/18 Digital volume correlation Number of projections X-ray computed tomography FDK algorithm
	Theoretical Design and FPGA-Based Implementation of Higher-Dimensional Digital Chaotic Systems 期刊论文 OAI收割 IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS, 2016, 卷号: 63, 期号: 3, 页码: 401-412 作者: Wang, Qianxue; Yu, Simin; Li, Chengqing; Lu, Jinhu; Fang, Xiaole \| 收藏 \| 浏览/下载：27/0 \| 提交时间：2018/07/30 Chaotic encryption dynamical degradation FPGA implementation high-dimensional digital chaotic system random number generator
	Fractal Characteristics of Visible Spectra Across a Hilly Area 期刊论文 OAI收割 SPECTROSCOPY AND SPECTRAL ANALYSIS, 2011, 卷号: 31, 期号: 2, 页码: 473-477 作者: Zhang Fa-sheng; Liu Zuo-xin; Wan Hao-lei; Liu Miao \| 收藏 \| 浏览/下载：19/0 \| 提交时间：2019/06/04 Digital Number Scale-invariance Multifractal Analysis Spatial Heterogeneity
	Method of auto multi-exposure for high dynamic range imaging (EI CONFERENCE) 会议论文 OAI收割 2010 International Conference on Computer, Mechatronics, Control and Electronic Engineering, CMCE 2010, August 24, 2010 - August 26, 2010, Changchun, China Piao Y.; Xu W. 收藏 \| 浏览/下载：19/0 \| 提交时间：2013/03/25 This paper proposes a method for calculating the multi-exposure times fast and accurately when the scene has a high dynamic range minimizing the pictures needed to take and improving the dynamic range of the CCD system. The proposed method first measures the camera's response function referring [10]. After that the median value of the output picture is adjusted to be in the middle range of the system output by changing the exposure time. It can be inferred from the histogram of the current picture whether it's a high dynamic range scene by calculating the number of pixels under exposed and over exposed. Once again the under and over exposed pixels are adjusted to be in the middle according to the camera's response function. Finally different exposed pictures (2 or 3) are fused together by Gaussian function and the dynamic range is compressed by y correction. Experimental results on UNIQ-UM400 analog camera and a digital acquisition system show that the algorithm works well and solve the problem of low dynamic range of CCD camera. 2010 IEEE.
	Space camera imaging gain in-orbit adjusting strategy (EI CONFERENCE) 会议论文 OAI收割 2009 2nd International Conference on Intelligent Computing Technology and Automation, ICICTA 2009, October 10, 2009 - October 11, 2009, Changsha, Hunan, China 作者: Wang J.; He X. 收藏 \| 浏览/下载：17/0 \| 提交时间：2013/03/25 A Multi-Step Gain Adjusting Strategy (MSGAS) of space camera was proposed which was used to get higher SNR (Signal-Noise Rate) image. When the space camera working in poor light condition the CCD signal was so weak that it's difficult to get a clear image to reduce the quantization noise and improve the SNR we must amplify the CCD signal first and then quantize. The MSGAS was achieved by adjusting the gain of the CCD (Charge Couple Device) signal processor step by step the upper limit and lower limit were set if the MDN (Mean Digital Number) of a fixed length image data was not between the lower and upper limit the gain was adjusted step by step. In the experiment the upper limit lower limit and the step were set and the result of the experiment showed that MSGAS was robust and SNR was improved from 28 to 39. 2009 IEEE.
	Lossless wavelet compression on medical image (EI CONFERENCE) 会议论文 OAI收割 4th International Conference on Photonics and Imaging in Biology and Medicine, September 3, 2005 - September 6, 2005, Tianjin, China 作者: Liu H.; Liu H.; Liu H. 收藏 \| 浏览/下载：41/0 \| 提交时间：2013/03/25 An increasing number of medical imagery is created directly in digital form. Such as Clinical image Archiving and Communication Systems (PACS). as well as telemedicine networks require the storage and transmission of this huge amount of medical image data. Efficient compression of these data is crucial. Several lossless and lossy techniques for the compression of the data have been proposed. Lossless techniques allow exact reconstruction of the original imagery while lossy techniques aim to achieve high compression ratios by allowing some acceptable degradation in the image. Lossless compression does not degrade the image thus facilitating accurate diagnosis of course at the expense of higher bit rates i.e. lower compression ratios. Various methods both for lossy (irreversible) and lossless (reversible) image compression are proposed in the literature. The recent advances in the lossy compression techniques include different methods such as vector quantization wavelet coding neural networks and fractal coding. Although these methods can achieve high compression ratios (of the order 50:1 or even more) they do not allow reconstructing exactly the original version of the input data. Lossless compression techniques permit the perfect reconstruction of the original image but the achievable compression ratios are only of the order 2:1 up to 4:1. In our paper we use a kind of lifting scheme to generate truly loss-less non-linear integer-to-integer wavelet transforms. At the same time we exploit the coding algorithm producing an embedded code has the property that the bits in the bit stream are generated in order of importance so that all the low rate codes are included at the beginning of the bit stream. Typically the encoding process stops when the target bit rate is met. Similarly the decoder can interrupt the decoding process at any point in the bil stream and still reconstruct the image. Therefore a compression scheme generating an embedded code can start sending over the network the coarser version of the image first and continues with the progressive transmission of the refinement details. Experimental results show that our method can get a perfect performance in compression ratio and reconstructive image.
	Measuring the system gain of the TDI CCD remote sensing camera (EI CONFERENCE) 会议论文 OAI收割 Advanced Materials and Devices for Sensing and Imaging II, November 8, 2004 - November 10, 2004, Beijing, China Ya-xia L.; Hai-ming B.; Jie L.; Jin R.; Zhi-hang H. 收藏 \| 浏览/下载：62/0 \| 提交时间：2013/03/25 The gain of a TDI CCD camera is the conversion between the number of electrons recorded by the TDI CCD and the number of digital units (counts) contained in the CCD image"[1]. TDI CCD camera has been a main technical approach for meeting the requirements of high-resolution and lightweight of remote sensing equipment. It is useful to know this conversion for evaluating the performance of the TDI CCD camera. In general a lower gain is better. However the resulting slope is the gain of the TDI CCD. We did the experiments using the Integration Sphere in order to get a flat field effects. We calculated the gain of the four IT-EI-2048 TDI CCD. The results and figures of the four TDI CCD are given. this is only true as long as the total well depth (number of electrons that a pixel can hold) of the pixels can be represented. High gains result in higher digitization noise. System gains are designed to be a compromise between the extremes of high digitization noise and loss of well depth. In this paper the mathematical theory is given behind the gain calculation on a TDI CCD camera and shows how the mathematics suggests ways to measure the gain accurately according to the Axiom Tech. The gains were computed using the mean-variance method also known as the method of photon transfer curves. This method uses the effect of quantization on the variance in the measured counts over a uniformly illuminated patch of the detector. This derivation uses the concepts of signal and noise. A linear fit is done of variance vs. mean