Results 231 to 240 of about 36,154 (265)

Blurred Image Restoration Using Fast Blur-Kernel Estimation

2014 Tenth International Conference on Intelligent Information Hiding and Multimedia Signal Processing, 2014
Motion blur is usually generated when people captured a picture in the daily life. This kind of blur is often non-liner motion and may cause the blurred contents seriously in this image. Hence, how to remove the blurred image into a clear image becomes a very important scheme.
Hui-Yu Huang, Wei-Chang Tsai
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Restoration of the Blurred Image Based on Continuous Blur Kernel

2016 8th International Conference on Intelligent Human-Machine Systems and Cybernetics (IHMSC), 2016
It's very common to see many regions of the blur in the pictures because of the relative movement of the subject and the shooting equipment, which causes much difficulty for the subsequent processing such as information extraction. This paper proposes a new method to solve the problem by using the continuous motion kernel.
Yuanzhi Gong, Yule Yuan, Wenbin Zou, Yong Zhao, Song Tang, Yuanyuan Qin   +5 more
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Exposing Blur Kernel from Retouch Image

2013 International Conference on Computer-Aided Design and Computer Graphics, 2013
The blurring in image comes either from the acquisition noise, or from image editing operation. The produced adverse noise during acquisition need to be eliminated, and the blurring generated by editing should be known in digital forensics, so the blur kernel recovery is significant in community of image processing and computer graphics.
Zhenlong Du, Xiaoli Li 0005, Yanwen Guo 0001   +2 more
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Blur kernel estimation using the radon transform

CVPR 2011, 2011
Camera shake is a common source of degradation in photographs. Restoring blurred pictures is challenging because both the blur kernel and the sharp image are unknown, which makes this problem severely underconstrained. In this work, we estimate camera shake by analyzing edges in the image, effectively constructing the Radon transform of the kernel ...
Taeg Sang Cho, Sylvain Paris, Berthold K. P. Horn, William T. Freeman   +3 more
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Improved blur kernel estimation with blurred and noisy image pairs

2010 International Conference on Computer and Communication Technologies in Agriculture Engineering, 2010
In this paper, we propose a TV-L1 denoising model-based kernel estimation in image deblurring which uses both blurred and noisy images. More details and edges are recovered in the denoised image which is used to replace the true image and do the deconvolution.
null Qian Wan, null Yuan-Biao Zhang, null Chuan He, null Jia-Di Wan   +3 more
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Space-varying blur kernel estimation and image deblurring

SPIE Proceedings, 2014
In recent years, we have seen highly successful blind image deblurring algorithms that can even handle large motion blurs. Most of these algorithms assume that the entire image is blurred with a single blur kernel. This assumption does not hold if the scene depth is not negligible or when there are multiple objects moving differently in the scene ...
Qinchun Qian, Bahadir K. Gunturk
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A Learnable Blur Kernel for Remote Sensing Image Retrieval

IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium, 2020
With the explosive increase of remote sensing images, content-based remote sensing image retrieval (CBRSIR) has aroused widespread attention. Convolutional Neural Network (CNN) based methods are widely used in CBRSIR due to the development of deep learning. However, common used CNN models have difficulties in holding shift-invariant property due to the
Zelin Peng, Guanchun Wang, Xiangrong Zhang, Xu Tang, Li Gao, Licheng Jiao   +5 more
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Multiframe image restoration in the presence of noisy blur kernel

2009 16th IEEE International Conference on Image Processing (ICIP), 2009
We wish to recover an original image u from several blurry-noisy versions f k , called frames. We assume a more severe degradation model, in which the image u has been blurred by a noisy (stochastic) point spread function. We consider the problem of restoring the degraded image in a variational framework. Since the recovery of u from one single frame f
Miyoun Jung, Antonio Marquina, Luminita A. Vese   +2 more
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Image deblurring with blur kernel estimation in RGB channels

2016 IEEE International Conference on Digital Signal Processing (DSP), 2016
Image deblurring aims to recover the clear image from the damaged image. The most existing blind image de-blurring approaches only consider estimating the blur kernel in the gray domain. In fact, for the color image produced by the digital camera, the blur effects for each color channel are usually different.
Xianqiu Xu, Hongqing Liu, Yong Li 0023, Yi Zhou 0014   +3 more
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Kernel-Based Motion-Blurred Target Tracking

2011
Motion blurs are pervasive in real captured video data, especially for hand-held cameras and smartphone cameras because of their low frame rate and material quality. This paper presents a novel Kernel-based motion-Blurred target Tracking (KBT) approach to accurately locate objects in motion blurred video sequence, without explicitly performing ...
Yi Wu 0001, Jing Hu, Feng Li 0005, Erkang Cheng, Jingyi Yu, Haibin Ling   +5 more
openaire   +1 more source