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	Temperature control characteristics analysis of lead-cooled fast reactor with natural circulation 期刊论文 OAI收割 ANNALS OF NUCLEAR ENERGY, 2016, 卷号: 90, 期号: 无, 页码: 54-61 作者: Yang, Minghan; Song, Yong; Wang, Jianye; Xu, Peng; Zhang, Guangyu \| 收藏 \| 浏览/下载：17/0 \| 提交时间：2018/01/25 Lfr Natural Circulation Temperature Control Characteristic Transfer Function Matrix Frequency Domain Analysis Method
	Adaptive Wiener filtering with Gaussian fitted point spread function in image restoration (EI CONFERENCE) 会议论文 OAI收割 2011 IEEE 2nd International Conference on Software Engineering and Service Science, ICSESS 2011, July 15, 2011 - July 17, 2011, Beijing, China 作者: Yang L.; Zhang X.; Zhang X.; Zhang X.; Yang L. 收藏 \| 浏览/下载：41/0 \| 提交时间：2013/03/25 In the imaging process of the space remote sensing camera there was degradation phenomenon in the acquired images. In order to reduce the image blur caused by the degradation the remote sensing images were restored to give prominence to the characteristic objects in the images. First the frequency-domain notch filter was adopted to remove strip noises in the images. Then using the ground characters with the knife-edge shape in the images the point spread function of the imaging system was estimated. In order to improve the accuracy the estimated point spread function was corrected with Gaussian fitting method. Finally the images were restored using the adaptive Wiener filtering with the fitted point spread function. Experimental results of the real remote sensing images showed that almost all strip noises in the images were eliminated. After the denoised images were restored its variance and its gray mean gradient increased also its laplacian gradient increased. Restoration with Gaussian fitted point spread function is beneficial to interpreting and analyzing the remote sensing images. After restoration the blur phenomenon of the images is reduced. The characters are highlighted and the visual effect of the images is clearer. 2011 IEEE.
	MTF-based research on the minimum fill factor in optical sparse aperture system (EI CONFERENCE) 会议论文 OAI收割 2011 4th International Conference on Intelligent Computation Technology and Automation, ICICTA 2011, March 28, 2011 - March 29, 2011, Shenzhen, Guangdong, China 作者: Liu Z. 收藏 \| 浏览/下载：27/0 \| 提交时间：2013/03/25 To avoid the loss of image information when it is transferred through optical sparse aperture system with excessively diluted apertures arrangement we propose a method in the frequency domain termed characteristic triangle to calculate the minimum fill factor. This method is based on the characteristics of MTF and demonstrates that when the characteristic triangle is equilateral with each side 3th power of sub-MTF cutoff frequency MTF has no zero value below cutoff frequency thus we can obtain the minimum fill factor. Furthermore we apply it to some typical sparse arrays such as Golay3 Golay6 Ring6 and Tri-arm7 and get their fill factors of 33.33% 15.16% 30.11% and 11.14% correspondingly which are consistent with numerical results. 2011 IEEE.
	Cr image enhancement based on human visual characteristics (EI CONFERENCE) 会议论文 OAI收割 2010 International Conference on Computer Design and Applications, ICCDA 2010, June 25, 2010 - June 27, 2010, Qinhuangdao, Hebei, China Zhang M.-H.; Zhang Y.-Y. 收藏 \| 浏览/下载：28/0 \| 提交时间：2013/03/25 The characteristic of digital CR medicine radiation image has wide dynamic range abundant details and bad contrast so it is necessary to enhance CR image to the need of doctor diagnosis. But the general enhancement algorithms don't consider human visual characteristics so it puts forward CR medicine image adaptive enhancement algorithm combining the human visual property which is more sensitive to smooth area noise compared with detail area noise and makes image edge detail enhancement great in detail area and detail enhancement little in smooth area in which factor K is based on space change of image domain accordingly gaining non-linear enhancement edge details of CR image. Experiment results demonstrate that the algorithm enhances CR image detail and CR image enhanced has good visual effect so the method is fit for edge detail enhancement of CR medicine radiation image. 2010 IEEE.
	飞秒脉冲通过散射表面后的时域特性期刊论文 OAI收割中国激光, 2009, 卷号: 36, 期号: 5, 页码: 1160-1165 刘文军; 任守田; 曲士良; 戴恩文; 周常河收藏 \| 浏览/下载：1244/159 \| 提交时间：2010/05/14 散射时域特性频率分辨光学开关法飞秒脉冲散射表面 scattering time domain characteristic frequency-resolved optical gating femtosecond pulse scattering surface
	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：35/0 \| 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.