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	Accurate and Fast Image Denoising via Attention Guided Scaling 期刊论文 OAI收割 IEEE TRANSACTIONS ON IMAGE PROCESSING, 2021, 卷号: 30, 页码: 6255-6265 作者: Zhang, Yulun; Li, Kunpeng; Li, Kai; Sun G(孙干); Kong, Yu \| 收藏 \| 浏览/下载：31/0 \| 提交时间：2021/08/03 Image denoising Noise measurement Training Noise reduction Generative adversarial networks Visualization Task analysis Image denoising attention guided scaling feature collection and distribution object recognition semantic segmentation
	Experimental study of the air-knife thermal control system for a large-aperture primary mirror 会议论文 OAI收割 Hefei, China, November 26, 2018 - November 28, 2018 作者: Tan, Yufeng; Wang, Jihong; Ren, Ge; Xie, Zongliang; Ren, Xiaoli \| 收藏 \| 浏览/下载：22/0 \| 提交时间：2021/05/06 scaling experiment lightweighted mirror image quality thermal control
	Rotation Scaling and Translation Invariants of 3D Radial Shifted Legendre Moments 期刊论文 OAI收割 International Journal of Automation and Computing, 2018, 卷号: 15, 期号: 2, 页码: 169-180 作者: Mostafa El Mallahi; Jaouad El Mekkaoui; Amal Zouhri; Hicham Amakdouf; Hassan Qjidaa \| 收藏 \| 浏览/下载：14/0 \| 提交时间：2021/02/23 3D radial complex moments 3D radial shifted Legendre radial moments radial shifted Legendre polynomials 3D image reconstruction 3D rotation scaling translation invariants 3D image recognition computational complexities.
	图像和视频画面显示自适应技术研究学位论文 OAI收割工学博士, 中国科学院自动化研究所: 中国科学院大学, 2014 作者: 屈展收藏 \| 浏览/下载：56/0 \| 提交时间：2015/09/02 图像和视频自适应变形裁切缩放显著性检测凸规划 Image and video retargeting warping cropping scaling salience map convex programming
	自动指纹识别技术的应用研究学位论文 OAI收割工学博士, 中国科学院自动化研究所: 中国科学院研究生院, 2012 作者: 陶训强收藏 \| 浏览/下载：158/0 \| 提交时间：2015/09/02 质量判断方向场模型指纹增强尺度缩放交叉匹配 ¯ ngerprint image quality measure orientation model image enhancement image scaling cross-matching
	Rotation and scaling invariant feature lines for image matching (EI CONFERENCE) 会议论文 OAI收割 2011 International Conference on Mechatronic Science, Electric Engineering and Computer, MEC 2011, August 19, 2011 - August 22, 2011, Jilin, China 作者: Wang Y.; Wang Y.; Wang Y.; Wang Y.; Wang Y. 收藏 \| 浏览/下载：28/0 \| 提交时间：2013/03/25 Image matching has been one of the most fundamental issues computer vision over the decades. In this paper we propose a novel method based on making use of feature lines in order to achieve more robust image matching. The feature lines have the properties of rotation and scaling invariance coined RIFLT(Rotation invariant feature line transform). Experimental results demonstrate the effectiveness and efficiency of the proposed method. Compare with the famous powerful algorithm Scale Invariant Feature Transform(SIFT) the proposed method is more insensitive to noise. And for certain sequence of images which contain clear lines the proposed method is more efficiency. Using the feature lines obtained by our method it is possible to matching two scene images with different rotation angles scale and light distort. 2011 IEEE.
	A new research of sub-pixel level accuracy of TDICCD remote sensing image registration (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 作者: He B. 收藏 \| 浏览/下载：24/0 \| 提交时间：2013/03/25 In the field of remote sensing imaging TDICCD remote sensing images have a lot of their own characteristics such as high-resolution large amount of information less overlapping parts of pixels additional image blurring etc. Therefore there exist many difficulties especially in terms of high-accuracy registration of pairs of images. For that this paper presents two new pixel interpolation method for sub-pixel level registering images that allows for scaling translation and rotation. The proposed technique which is based on the maximization of the correlation coefficient function combines an efficient pixel-moving interpolation scheme with surface fitting which greatly reduces the overall computational cost. The accuracy of the algorithm is evaluated by calculating correlation coefficient of couples of points belonging to images transformed with preset factors and also comparing it to other sorts of methods. The experiment results show that the accuracy of registration reaches 0.01 pixels. 2010 IEEE.
	Scene matching based on directional keylines and polar transform (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 作者: Wang Y.; Wang Y.; Wang Y.; Wang Y.; Wang Y. 收藏 \| 浏览/下载：24/0 \| 提交时间：2013/03/25 Scene matching under complex background is a priority and difficulty in the field of computer vision it has the characteristics of rotation and scaling invariance commonly used in matching real-time collected images and photos for navigation. Scene matching techniques are faced with complex natural scenes anti-light and anti-slight-distortion the image distortion exist applicable for complex scene matching. The project has a new idea: combining the keylines with the vectors description based on polar image translation such as light and utilize the rotation-scale-invariance vectors to describe the extracted keylines change of gray levels this method includes three steps: keylines extraction perspective description and matching. Preliminary experiments show that this keylines-based scene matching algorithm is applicable for image matching under complex background. 2010 IEEE. scaling and other differences which cause matching difficult. This paper aims to find a scene matching algorithm
	An object recognition method based on fuzzy theory and BP networks (EI CONFERENCE) 会议论文 OAI收割 ICO20: Optical Information Processing, August 21, 2005 - August 26, 2005, Changchun, China Chuan W.; Ming Z.; Dong Y. 收藏 \| 浏览/下载：21/0 \| 提交时间：2013/03/25 It is difficult to choose eigenvectors when neural network recognizes object. It is possible that the different object eigenvectors is similar or the same object eigenvectors is different under scaling shifting rotation if eigenvectors can not be chosen appropriately. In order to solve this problem the image is edged the membership function is reconstructed and a new threshold segmentation method based on fuzzy theory is proposed to get the binary image. Moment invariant of binary image is extracted and normalized. Some time moment invariant is too small to calculate effectively so logarithm of moment invariant is taken as input eigenvectors of BP network. The experimental results demonstrate that the proposed approach could recognize the object effectively correctly and quickly.