Results 131 to 140 of about 547 (178)
Some of the next articles are maybe not open access.
Blind Deblurring for Saturated Images
2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021Blind deblurring has received considerable attention in recent years. However, state-of-the-art methods often fail to process saturated blurry images. The main reason is that pixels around saturated regions are not conforming to the commonly used linear blur model.
Liang Chen 0026 +4 more
openaire +2 more sources
Blind and Semi-Blind Deblurring of Natural Images
IEEE Transactions on Image Processing, 2010A method for blind image deblurring is presented. The method only makes weak assumptions about the blurring filter and is able to undo a wide variety of blurring degradations. To overcome the ill-posedness of the blind image deblurring problem, the method includes a learning technique which initially focuses on the main edges of the image and gradually
Luis Almeida, Mariana S C Almeida
exaly +4 more sources
Blind Image Deblurring With Gaussian Curvature of the Image Surface
Signal Processing: Image Communication, 2022Abstract This paper presents a blind image deblurring algorithm by utilizing Gaussian curvature (GC) of the image surface. GC is an intrinsic geometric feature and related to the developability of the surface. In recent years, numerous variational models based on GC for image denoising and image reconstruction have been proposed.
Xianyu Ge, Jieqing Tan, Dandan Hu
exaly +2 more sources
2021 6th International Conference for Convergence in Technology (I2CT), 2021
With the growth of technology and digital media, images have started playing a critical role not only in our day-to-day lives but also in fields like Biology and Astronomy to name a few. However, images prove to be useful only when they can successfully convey information to a viewer.
Vahida Attar +3 more
openaire +1 more source
With the growth of technology and digital media, images have started playing a critical role not only in our day-to-day lives but also in fields like Biology and Astronomy to name a few. However, images prove to be useful only when they can successfully convey information to a viewer.
Vahida Attar +3 more
openaire +1 more source
2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017
We present a novel approach to noise-blind deblurring, the problem of deblurring an image with known blur, but unknown noise level. We introduce an efficient and robust solution based on a Bayesian framework using a smooth generalization of the 0-1 loss. A novel bound allows the calculation of very high-dimensional integrals in closed form.
Meiguang Jin, Stefan Roth, Paolo Favaro
openaire +2 more sources
We present a novel approach to noise-blind deblurring, the problem of deblurring an image with known blur, but unknown noise level. We introduce an efficient and robust solution based on a Bayesian framework using a smooth generalization of the 0-1 loss. A novel bound allows the calculation of very high-dimensional integrals in closed form.
Meiguang Jin, Stefan Roth, Paolo Favaro
openaire +2 more sources
Blind face images deblurring with enhancement
Multimedia Tools and Applications, 2020Face images deblurring has achieved advanced development; however, existing methods involve high computational cost problems. Furthermore, the recovered face images by current methods have the problems of over-smooth textures, ringing artifacts, and poor details. We consider the problem of face images deblurring as a semantic generation task.
Qing Qi +3 more
openaire +1 more source
Blind deblurring of spiral CT images
IEEE Transactions on Medical Imaging, 2001To discriminate fine anatomical features in the inner ear, it has been desirable that spiral computed tomography (CT) may perform beyond their current resolution limits with the aid of digital image processing techniques. In this paper, we develop a blind deblurring approach to enhance image resolution retrospectively without complete knowledge of the ...
Ming Jiang 0001 +4 more
openaire +3 more sources
A Deep Variational Bayesian Framework for Blind Image Deblurring
Knowledge-Based Systems, 2022 Blind image deblurring is an important yet very challenging problem in low-level vision. Traditional optimization based methods generally formulate this task as a maximum-a-posteriori estimation or variational inference problem, whose performance highly relies on the handcraft priors for both the latent image and the blur kernel.
Qian Zhao, Deyu Meng
exaly +3 more sources
Blind Image Deblurring with Outlier Handling
2017 IEEE International Conference on Computer Vision (ICCV), 2017Deblurring images with outliers has attracted considerable attention recently. However, existing algorithms usually involve complex operations which increase the difficulty of blur kernel estimation. In this paper, we propose a simple yet effective blind image deblurring algorithm to handle blurred images with outliers. The proposed method is motivated
Jiangxin Dong +3 more
openaire +2 more sources
A Comparative Study for Single Image Blind Deblurring
2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016Numerous single image blind deblurring algorithms have been proposed to restore latent sharp images under camera motion. However, these algorithms are mainly evaluated using either synthetic datasets or few selected real blurred images. It is thus unclear how these algorithms would perform on images acquired "in the wild" and how we could gauge the ...
Wei-Sheng Lai +2 more
exaly +3 more sources