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	The research of digltal CR medicine image adapitive enhancement method (EI CONFERENCE) 会议论文 OAI收割 4th International Conference on Mechanical and Electrical Technology, ICMET 2012, July 24, 2012 - July 26, 2012, Kuala Lumpur, Malaysia Ming-Hui Z.; Yao-Yu Z. 收藏 \| 浏览/下载：63/0 \| 提交时间：2013/03/25 Digital CR medicine radiation image is in doctor's favor and has became medicine imaging technology new hot spot because of its high gray contrast powerful computer disposal function little radiation dosage non-film diagnosis different area consultation. But degradation of digital X-ray medical image such as low contrast and blurring during radiographic imaging caused by complexity of body tissue and effects of X-ray scattering and electrical noise etc. can worsen the results of analysis and diagnosis. So it is usually needed that CR medicine image is enhanced to improve its vision quality and easy to doctor's more accurate diagnosis. The general enhancement algorithms over enhancing the contrast and lose image details aiming at the defects an enhancement algorithm for CR image is proposed based on the ratio of deviation to mean of domain. The arithmetic enhance CR image edge details by adjusting factor K based on the ratio of deviation to mean of domain of CR image. Experiment results demonstrate that the algorithm enhances CR image detail and CR image enhanced has good visual effect the adaptive enhancement method is fit for CR medicine image. (2012) Trans Tech Publications Switzerland.
	Research on infrared dim-point target detection and tracking under sea-sky-line complex background (EI CONFERENCE) 会议论文 OAI收割 International Symposium on Photoelectronic Detection and Imaging 2011: Advances in Infrared Imaging and Applications, May 24, 2011 - May 24, 2011, Beijing, China 作者: Dong Y.-X.; Zhang H.-B.; Li Y.; Li Y.; Li Y. 收藏 \| 浏览/下载：109/0 \| 提交时间：2013/03/25 Target detection and tracking technology in infrared image is an important part of modern military defense system. Infrared dim-point targets detection and recognition under complex background is a difficulty and important strategic value and challenging research topic. The main objects that carrier-borne infrared vigilance system detected are sea-skimming aircrafts and missiles. Due to the characteristics of wide field of view of vigilance system the target is usually under the sea clutter. Detection and recognition of the target will be taken great difficulties.There are some traditional point target detection algorithms such as adaptive background prediction detecting method. When background has dispersion-decreasing structure the traditional target detection algorithms would be more useful. But when the background has large gray gradient such as sea-sky-line sea waves etc.The bigger false-alarm rate will be taken in these local area.It could not obtain satisfactory results. Because dim-point target itself does not have obvious geometry or texture feature in our opinion from the perspective of mathematics the detection of dim-point targets in image is about singular function analysis.And from the perspective image processing analysis the judgment of isolated singularity in the image is key problem. The foregoing points for dim-point targets detection its essence is a separation of target and background of different singularity characteristics.The image from infrared sensor usually accompanied by different kinds of noise. These external noises could be caused by the complicated background or from the sensor itself. The noise might affect target detection and tracking. Therefore the purpose of the image preprocessing is to reduce the effects from noise also to raise the SNR of image and to increase the contrast of target and background. According to the low sea-skimming infrared flying small target characteristics the median filter is used to eliminate noise improve signal-to-noise ratio then the multi-point multi-storey vertical Sobel algorithm will be used to detect the sea-sky-line so that we can segment sea and sky in the image. Finally using centroid tracking method to capture and trace target. This method has been successfully used to trace target under the sea-sky complex background. 2011 Copyright Society of Photo-Optical Instrumentation Engineers (SPIE).
	Detection of low contrast targets based on lifting scheme wavelet transform (EI CONFERENCE) 会议论文 OAI收割 2009 IEEE International Conference on Mechatronics and Automation, ICMA 2009, August 9, 2009 - August 12, 2009, Changchun, China 作者: Chen X.; Wang Y.; Wang Y.; Wang Y.; Wang Y. 收藏 \| 浏览/下载：16/0 \| 提交时间：2013/03/25 This paper present a fast algorithm for detection of low contrast objects by using wavelet filters based on lifting scheme. The advantage is robust to noise. According Swelden's lifting wavelet filters are biorthogonal wavelet filters containing free parameters. We use reference image of targets to train the lifting terms so that the learnt wavelet filters have the features of targets. Then applying such filters to the images including targets taken from camera system. We can detect the locations where the high frequency components are almost the same as those of the target image. 2009 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：31/0 \| 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.