Multi-planar geometry and latent image recovery from a single motion-blurred image

2021 ◽  
Vol 33 (1) ◽  
Author(s):  
Kuldeep Purohit ◽  
Subeesh Vasu ◽  
M. Purnachandra Rao ◽  
A. N. Rajagopalan
Keyword(s):  
Image Recovery ◽  
Planar Geometry ◽  
Latent Image ◽  
Blurred Image

scholarly journals An Efficient Blind Image Deblurring Using a Smoothing Function

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Kittiya Khongkraphan ◽  
Aniruth Phonon ◽  
Sainuddeen Nuiphom
Keyword(s):  
Splitting Method ◽  
Closed Form Solution ◽  
Kernel Estimation ◽  
Image Deblurring ◽  
Form Solution ◽  
Smoothing Function ◽  
Image Method ◽  
Latent Image ◽  
Blind Image Deblurring ◽  
Blurred Image

This paper introduces an efficient deblurring image method based on a convolution-based and an iterative concept. Our method does not require specific conditions on images, so it can be widely applied for unspecific generic images. The kernel estimation is firstly performed and then will be used to estimate a latent image in each iteration. The final deblurred image is obtained from the convolution of the blurred image with the final estimated kernel. However, image deblurring is an ill-posed problem due to the nonuniqueness of solutions. Therefore, we propose a smoothing function, unlike previous approaches that applied piecewise functions on estimating a latent image. In our approach, we employ L2-regularization on intensity and gradient prior to converging to a solution of the deblurring problem. Moreover, our work is based on the quadratic splitting method. It guarantees that each subproblem has a closed-form solution. Various experiments on synthesized and real-world images confirm that our approach outperforms several existing methods, especially on the images corrupted by noises. Moreover, our method gives more reasonable and more natural deblurred images than those of other methods.

Blurred image recovery by a phase-processing method with tilt correction

2005 ◽  
Vol 44 (20) ◽  
pp. 4323
Author(s):  
Tadashi Aruga ◽  
Yasuharu Kohyama
Keyword(s):  
Processing Method ◽  
Image Recovery ◽  
Tilt Correction ◽  
Blurred Image

Attention guided complementary feature integration for latent image recovery from noisy/blurry pairs

2021 ◽  
Author(s):  
Green Rosh K S ◽  
Sachin Lomte ◽  
Nikhil Krishnan ◽  
B H Pawan Prasad
Keyword(s):  
Feature Integration ◽  
Image Recovery ◽  
Latent Image

scholarly journals Deblurring Method for Motion Blurred Images based on GAN

2021 ◽  
Vol 15 ◽  
pp. 106-113
Author(s):  
Ning Li ◽  
Songnan Chen ◽  
Mengxia Tang ◽  
Jiangming Kan
Keyword(s):  
Mobile Device ◽  
Network Structure ◽  
A Priori ◽  
Image Motion ◽  
Image Recovery ◽  
Generative Adversarial Network ◽  
Adversarial Network ◽  
Blurred Image ◽  
Evaluation Metric ◽  
Blurred Images

The purpose of image motion deblur is to recover the underlying clear image from the corresponding blur image. In most traditional methods, the image recovery task is formulated as a problem of blur core estimation and use a priori to calculate. In this paper we proposes a generative adversarial network(GAN) model based on the mobilenet-V3 network structure to meet the needs of motion blurred image recovery on mobile devices. Based on traditional evaluation indicators, we propose a new evaluation metric on mobile device. Extensive experiments show that our method is superior to the competing methods.

Estimation of PSF Using Logarithmic Amplitude Spectrum and Restoration of Blurred Image

2012 ◽  
Vol 132 (2) ◽  
pp. 284-290
Author(s):  
Yuka Nagashima ◽  
Shigeru Omatu ◽  
Michifumi Yoshioka
Keyword(s):  
Amplitude Spectrum ◽  
Blurred Image
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