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	Removing Random-Valued Impulse Noises by a Two-Staged Nonlinear Filtering Method 期刊论文 OAI收割 Transactions of Nanjing University of Aeronautics and Astronautics, 2016, 卷号: 33, 期号: 3, 页码: 329-338 作者: Ahmad Ashfaq; Lu Yanting 收藏 \| 浏览/下载：22/0 \| 提交时间：2017/01/17 image de-noising random-valued impulse noise nonlinear filter noisy pixel detection two-stage detection and correction method directional differences
	基于RGB-D的室外行人检测研究学位论文 OAI收割工学硕士, 中国科学院自动化研究所: 中国科学院大学, 2015 朱新亮收藏 \| 浏览/下载：110/0 \| 提交时间：2015/09/02 行人检测 RGB-D 图像配准深度图像去噪 Pedestrian Detection RGB-D Image Registration Depth Image De-noising
	Far-field focusing of laser beam based on digital image processing techniques (EI CONFERENCE) 会议论文 OAI收割 Optoelectronic Imaging and Multimedia Technology, October 18, 2010 - October 20, 2010, Beijing, China 作者: Zhao S.; Tian Y.-Z.; Liu L.-S.; Guo J.; Zhang H.-Y. 收藏 \| 浏览/下载：28/0 \| 提交时间：2013/03/25 In order to lead the laser beam transmit in the atmosphere convergently an experiment of laser focus at the distance of 450m and 300m has been operated in the outdoor place. The actual manipulations are as follows: Firstly the laser was collimated by a beam expander then the near-parallel laser beam was transmitted with a Galileo telescope system and the distance between the concave lens and the convex lens can be tuned through a precise displacement platform so the focus of the system changed due to the tiny displacement of the concave lens. Secondly the average power of the laser spot can be measured using power meter the power is 47.67mW and the standard deviation is 0.67mW while the focal length is 450m. Thirdly the energy distribution was found through the laser beam analyzer. The spot images were saved using the beam analyzer then the saved image can be processed with Matlab software afterwards. The function named EDGE and Sobel operator was used in the pre-processing of the saved image then method of median filter was used in the course of image de-noising and 53H filter was adopted in the signal analysis. The diameter of laser spot was obtained by the method above the diameter is 5.56mm and the standard deviation is 0.24mm. The spot center excursion is 0.56mm it is 10.43% of the total diameter of the laser spot. At last the key factors of the energy dissipation in the focusing system can be summarized as follows: restriction of the diffraction limit attenuation in the atmosphere geometrical aberration of optical system and the diffraction limit and the geometrical aberration are significant in the three factors above so we can reduce the impact of the both factors during the design of optical system. The reliable referenced data of the system design can be acquired through the primary experiment research. 2010 SPIE.
	Adaptive segmentation algorithm for ship target under complex background (EI CONFERENCE) 会议论文 OAI收割 2010 3rd International Conference on Advanced Computer Theory and Engineering, ICACTE 2010, August 20, 2010 - August 22, 2010, Chengdu, China Wang A.-B.; Wang C.-X.; Su W.-X.; Dong Y.-F. 收藏 \| 浏览/下载：31/0 \| 提交时间：2013/03/25 Segmentation of ship target under complex background has important research significance in long-range ship tracking and identification and an adaptive segmentation algorithm is proposed according to background images with different complexity. Local complexity of image is first calculated in this algorithm and then the original image is preprocessed with different de noising methods according to local complexity finally the image is binarized based on local complexity and the target is segmented. The experiment results indicate that the algorithm is adaptive and can meet the requirements of real-time processing which lays a foundation for ship target detection under complex background. 2010 IEEE.
	A nonlinear image enhancement algorithm based on partial differential equations (EI CONFERENCE) 会议论文 OAI收割 2010 IEEE 10th International Conference on Signal Processing, ICSP2010, October 24, 2010 - October 28, 2010, Beijing, China Han X.; Jian Z. 收藏 \| 浏览/下载：24/0 \| 提交时间：2013/03/25 Image enhancement and image de-noising have being the important research contents of image academic and engineering field and the partial differential equations have been widely applied to computer vision. The paper applies the thoughts of partial differential equations puts forward a new improved method of image enhancement. This method can enhance not only the dark images but also the bright images making the details hidden in the dark background and the bright background very clear. The application scope is wider and the visual effect is better. This paper uses the finite difference method to discrete the partial differential equations and combines with the heat equation. It calculates simple runs fast and provides a guarantee for real-time video image enhancement processing. 2010 IEEE.
	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：44/0 \| 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.