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Camera intrinsic blur kernel estimation: A reliable framework
2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015This paper presents a reliable non-blind method to measure intrinsic lens blur. We first introduce an accurate camera-scene alignment framework that avoids erroneous homography estimation and camera tone curve estimation. This alignment is used to generate a sharp correspondence of a target pattern captured by the camera.
Ali Mosleh 0002 +4 more
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Designing the optimal convolution kernel for modeling the motion blur
SPIE Proceedings, 2011Motion blur acts on an image like a two dimensional low pass filter, whose spatial frequency characteristic depends both on the trajectory of the relative motion between the scene and the camera and on the velocity vector variation along it. When motion during exposure is permitted, the conventional, static notions of both the image exposure and the ...
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Method to detect and calculate motion blur kernel
SPIE Proceedings, 2010Motion during camera's exposure time causes image blur, we call it motion blur. According to the linear system theory, if we can find the blur kernel which has the same meaning of point spread function, the blurred image can be restored by the blur kernel using iterative algorithms, such as R-L (Richardson-Lucy).
Jiagu Wu +4 more
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Joint blur kernel estimation and CNN for blind image restoration
Neurocomputing, 2020Xia Yousheng, Liqing Huang
exaly
Robust Blur Kernel Estimation for License Plate Images From Fast Moving Vehicles
IEEE Transactions on Image Processing, 2016Wengang Zhou, Houqiang Li, Qingbo Lu
exaly
Gaussian second derivative blur kernels for image deblurring
Digital Signal ProcessingGuoxing Huang +4 more
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Image deblurring based on double blur kernel
5th International Conference on Information Science, Electrical, and Automation Engineering (ISEAE 2023), 2023openaire +1 more source