Results 91 to 100 of about 12,142,372 (124)

Gaussian blurring-deblurring for improved image compression

, 2003
The deblurring of Gaussian blur by inverting the action of the diffusion equation has long been known. This technique is interesting but without much practical application since the images have to be blurred by convolution with a Gaussian to be "de ...
Bister, Michel, Yap, Moi Hoon, Ewe, Hong Tat   +2 more
core   +1 more source

Deep Lidar-Guided Image Deblurring

Sensors
The rise in portable Lidar instruments enables new opportunities for depth-assisted image processing. In this paper, we study whether the depth information provided by mobile Lidar sensors present in recent smartphones is useful for the task of image ...
Ziyao Yi, Diego Valsesia, Tiziano Bianchi, Enrico Magli   +3 more
doaj   +1 more source

Recent Progress in Image Deblurring [PDF]

This paper comprehensively reviews the recent development of image deblurring, including non-blind/blind, spatially invariant/variant deblurring techniques.
Wang, R, Tao, D
core  

Blind Remote Sensing Image Deblurring Based on Local Maximum High-Frequency Coefficient Prior and Graph Regularization

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
In satellite remote sensing imaging, factors such as optical axis shift, image plane jitter, movement of the target object, and Earth's rotation can induce image blur.
Zhidan Cai, Ming Fang, Zhe Li, Jinyi Ming, Huimin Wang   +4 more
doaj   +1 more source

Defocus Image Deblurring Network with Defocus Map Estimation as Auxiliary Task

, 2021
Different from the object motion blur, the defocus blur is caused by the limitation of the cameras’ depth of field. The defocus amount can be characterized by the parameter of point spread function and thus forms a defocus map.
Liao, Q, Ma, H, Liu, S, Xue, J-H, Zhang, J   +4 more
core  

Gyro-based Neural Single Image Deblurring [PDF]

In this paper, we present GyroDeblurNet, a novel single image deblurring method that utilizes a gyro sensor to effectively resolve the ill-posedness of image deblurring.
Baek, Seung-Hwan, Rim, Jaesung, Yang, Heemin, Cho, Sunghyun, Lee, Seungyong   +4 more
core   +1 more source

Image Deblurring Method with Fractional-order Total Variation and Adaptive Regularization Parameters

工程科学与技术, 2018
In order to better recovery texture details of images, avoid the difficulty of selecting the regularization parameters when solving the image deblurring model, a novel non-blind image deblurring method by using fractional order TV (FOTV) and adaptive ...
Xiaomei YANG, Yuqing XIANG, Yanan LIU, Xiujuan ZHENG   +3 more
doaj  

Analysis of Image Deblurring Techniques with Variations in Gaussian Noise and Regularization factor [PDF]

, 2018
—Image blur is integral part of imaging system and it often ruin the resultant image, video signal and photograph. Image Deblurring and Restoration is necessary in digital image processing.  Many methods have been proposed in this regard and in this
Harale, Mukesh
core  

Stereoscopic video deblurring transformer

Scientific Reports
Stereoscopic cameras, such as those in mobile phones and various recent intelligent systems, are becoming increasingly common. Multiple variables can impact the stereo video quality, e.g., blur distortion due to camera/object movement.
Hassan Imani, Md Baharul Islam, Masum Shah Junayed, Md Atiqur Rahman Ahad   +3 more
doaj   +1 more source

HRGAN: High-Resolution Representation Learning for Image Deblurring

, 2020
Existing state-of-the-art single-image motion deblurring frameworks first encode the input image as a semantically rich low-resolution representation and then recover the high-resolution image from this representation. The network which generates an
Borsuk, Vasyl
core