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Research Progress on Color Image Quality Assessment. [PDF]
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Recursive Neural Network for Video Deblurring
IEEE Transactions on Circuits and Systems for Video Technology, 2021Video deblurring is still a challenging low-level vision task since spatio-temporal characteristics across both the spatial and temporal domains are difficult to model. In this article, to model the temporal information, we develop a non-local block which estimates inter-frame similarity and inter-frame difference.
Xiaoqin Zhang +3 more
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Gated Spatio-Temporal Attention-Guided Video Deblurring
2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021Video deblurring remains a challenging task due to the complexity of spatially and temporally varying blur. Most of the existing works depend on implicit or explicit alignment for temporal information fusion, which either increases the computational cost or results in suboptimal performance due to misalignment.
Maitreya Suin, A. N. Rajagopalan
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Endoscopic video deblurring via synthesis
2017 IEEE Visual Communications and Image Processing (VCIP), 2017Endoscopic videos have been widely used for stomach diagnoses. However, endoscopic devices often capture videos with motion blurs, due to the dimly-lit environment and the camera shakiness during the capturing, which severely disturbs the diagnoses. In this paper, we present a framework that can restore blurry frames by synthesizing image details from ...
Lingbing Peng +4 more
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Embedded real-time HD video deblurring
2014 IEEE High Performance Extreme Computing Conference (HPEC), 2014This paper explores a computational deblurring algorithm that will ultimately be implemented in an embedded system with a targeted form factor of 2″×2″×3″. The deblurring algorithm completes a Fourier filtering step followed by a wavelet transform denoising step on a 1080×1920 Bayer input 30 frame per second video feed.
Timothy J. Dysart +3 more
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Deep Video Deblurring Using Sharpness Features From Exemplars
IEEE Transactions on Image Processing, 2020Video deblurring is a challenging problem as the blur in videos is usually caused by camera shake, object motion, depth variation, etc. Existing methods usually impose handcrafted image priors or use end-to-end trainable networks to solve this problem.
Xinguang Xiang, Hao Wei, Jinshan Pan
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Fast deblurring in video super resolution
2016 IEEE 13th International Conference on Signal Processing (ICSP), 2016Multi-frame super resolution has been well studied in recent years, but blur kernel is always assumed to be known in video super resolution problem. Most blind deconvolution algorithm can both estimate the blur kernel and the sharp image. In this paper, we originally adopt a fast single image blind deconvolution algorithm in video super resolution to ...
Xueqing Yang, Tingting Fan
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Attention-based interpolation network for video deblurring
Neurocomputing, 2021Abstract Video deblurring is a challenging low-level vision task due to variant blur artifacts caused by factors such as depth variations, high-speed movements and camera shakes. Although significant efforts have been devoted to addressing this task, two challenges of capturing temporal patterns and spatial topologies still remain.
Xiaoqin Zhang +4 more
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