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	Optimum parameters of image preprocessing method for Shack-Hartmann wavefront sensor in different SNR condition 会议论文 OAI收割 Nanjing, PEOPLES R CHINANanjing, PEOPLES R CHINA, OCT 24-26, 2017OCT 24-26, 2017 作者: Wei, Ping; Li, Xinyang; Luo, Xi; Li, Jianfeng \| 收藏 \| 浏览/下载：50/0 \| 提交时间：2019/08/23 SH-WFS centroid method SNR Thresholding method Windowing method
	Comparison of permissible source region and multispectral data using efficient bioluminescence tomography method 期刊论文 OAI收割 JOURNAL OF BIOPHOTONICS, 2011, 卷号: 4, 期号: 11-12, 页码: 824-839 作者: Qin, Chenghu; Zhu, Shouping; Feng, Jinchao; Zhong, Jianghong; Ma, Xibo 收藏 \| 浏览/下载：29/0 \| 提交时间：2015/08/12 Optical molecular imaging bioluminescence tomography permissible source region spectrally resolved measurements iterative shrinkage thresholding method
	Electro-optical imaging system identification using pseudo-random binary pattern (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 Le Y.; Jian W.; Jianzhong Z.; Qiang S.; Jianzhuo L. 收藏 \| 浏览/下载：23/0 \| 提交时间：2013/03/25 A method using pseudo-random binary pattern is developed for electro-optical imaging system identification. The imaging system is taken as a stable linear time-invariant and causal filter and its transfer function is measured through the pseudo-random binary sequence impulse responses identification. A digital mirror device (DMD) light projector is developed as the target generator and wavelet thresholding is used to denoise the captured image. Pre-filtering spectral estimation algorithm with adaptive parameter selection is also proposed for the identification process overcoming the challenge brought by the size limit derived from the optical isoplantic region. Simulations and experiments are presented to show the effectiveness of the proposed method.0-64. 2010 IEEE.
	An improved two-dimensional entropy method for star trail tracing in deep sky (EI CONFERENCE) 会议论文 OAI收割 ICO20: Optical Information Processing, August 21, 2005 - August 26, 2005, Changchun, China 作者: Wang Y.-J.; Yao Z.-J. 收藏 \| 浏览/下载：32/0 \| 提交时间：2013/03/25 The trace of star trail is an important component of deep sky detection. The stars are low contrast targets and their self-rotation will make their brightness change in cycle. Above all the trail trace is vulnerable to the block and disturbance of other stars. Traditional one-dimensional maximum entropy thresholding algorithm is vulnerable to the noise and the calculation of two-dimensional entropy methods is too large and takes too much time. This paper proposes an improved two-dimensional entropy threshold algorithm. We use recursion iteration method to eliminate the redundancy calculation and reduce the size of two-dimensional histogram based on the deep sky stars characteristic such as low contrast fuzziness and the centralized histogram. We also combine our algorithm with the space trail trace model to forecast the star trace. Experiments results show when the star are blocked or they turn dark the method still can well extrapolate the star trace. Our method improves the capability of trailing the ebb and small star and increases the precision of tracing. It is also robust to the noise so there is a good application foreground for the method.
	A new approach for the removal of mixed noise based on wavelet transform (EI CONFERENCE) 会议论文 OAI收割 ICO20: Remote Sensing and Infrared Devices and Systems, August 21, 2005 - August 26, 2005, Changchun, China 作者: Li Y.; Li Y.; Li Y.; Li Y. 收藏 \| 浏览/下载：38/0 \| 提交时间：2013/03/25 This paper proposed a new approach for the removal of mixed noise. There are many different ways in image denoising. Donoho et al have proposed a method for image de-noising by thresholding ambiguity is often resulted in determining the correspondence of a modulus maximum to a singularity. In the light and indeed we combine the merits of the two techniques to form a new approach for the removal of mixed noise. At first the application of their method to image denoising has been extremely successful. But the method of Donoho is based on the assumption that the type of noise is only additive Gaussian noise we used wavelet singularity detection (WSD) technique to analyze singularities of signal and noise. According to the characteristic that wavelet transform modulus maxima of impulse noise rapidly decreases as the scale increases in wavelet domain which is not successful for impulse noise. Mallat has also presented a method for signal denoising by discriminating the noise and the signal singularities through an analysis of their wavelet transform modulus maxima (WTMM). Nevertheless it can be accurately located with multiscale space by going through dyadic orthogonal wavelet transform and removed. Furthermore the Gaussian noise is also removed through a level-dependent thresholding algorithm the tracing of WTMM is not just tedious procedure computationally algorithm. The experimental results demonstrate that the proposed method can effectively detect impulse noise and remove almost all of the noise while preserve image details very well.
	High-accuracy real-time automatic thresholding for centroid tracker (EI CONFERENCE) 会议论文 OAI收割 ICO20: Optical Information Processing, August 21, 2005 - August 26, 2005, Changchun, China 作者: Wang Y.; Wang Y.; Wang Y.; Wang Y.; Zhang Y. 收藏 \| 浏览/下载：37/0 \| 提交时间：2013/03/25 Many of the video image trackers today use the centroid as the tracking point. In engineering we can get several key pairs of peaks which can include the target and the background around it and use the method of Otsu to get intensity thresholds from them. According to the thresholds it give a great help for us to get a glancing size a target's centroid is computed from a binary image to reduce the processing time. Hence thresholding of gray level image to binary image is a decisive step in centroid tracking. How to choose the feat thresholds in clutter is still an intractability problem unsolved today. This paper introduces a high-accuracy real-time automatic thresholding method for centroid tracker. It works well for variety types of target tracking in clutter. The core of this method is to get the entire information contained in the histogram we can gain the binary image and get the centroid from it. To track the target so that we can compare the size of the object in the current frame with the former. If the change is little such as the number of the peaks the paper also suggests subjoining an eyeshot-window we consider the object has been tracked well. Otherwise their height just like our eyes focus on a target if the change is bigger than usual position and other properties in the histogram. Combine with this histogram analysis we will not miss it unless it is out of our eyeshot we should analyze the inflection in the histogram to find out what happened to the object. In general the impression will help us to extract the target in clutter and track it and we will wait its emergence since it has been covered. To obtain the impression what we have to do is turning the analysis into codes for the tracker to determine a feat threshold. The paper will show the steps in detail. The paper also discusses the hardware architecture which can meet the speed requirement. the paper offers a idea comes from the method of Snakes