Blind Deconvolution of Blurred Images with Fuzzy Size Detection of Point Spread Function

2012 ◽  
pp. 261-271
Author(s):  
Salman Hameed Khan ◽  
Muhammad Sohail ◽  
Ahmed Rehan ◽  
Zeashan Hameed Khan ◽  
Arsalan Hameed Khan
Keyword(s):  
Point Spread Function ◽  
Blind Deconvolution ◽  
Point Spread ◽  
Spread Function ◽  
Blurred Images

Multichannel Blind Deconvolution-Based on-Orbit Estimation of Point Spread Function for Space Optical Remote Sensors

2013 ◽  
Vol 33 (4) ◽  
pp. 0428001 ◽  
Author(s):  
郭玲玲 Guo Lingling ◽  
吴泽鹏 Wu Zepeng ◽  
张立国 Zhang Liguo ◽  
任建岳 Ren Jianyue
Keyword(s):  
Point Spread Function ◽  
Blind Deconvolution ◽  
Remote Sensors ◽  
Point Spread ◽  
Spread Function ◽  
Orbit Estimation

A Research on the Optimization of Fuzzy Image

2013 ◽  
Vol 409-410 ◽  
pp. 1593-1596
Author(s):  
Xue Feng Wu ◽  
Yu Fan
Keyword(s):  
Mathematical Model ◽  
Image Restoration ◽  
Point Spread Function ◽  
Motion Blur ◽  
Inverse Filtering ◽  
Point Spread ◽  
Spread Function ◽  
Blurred Image ◽  
Blurred Images ◽  
Fuzzy Image

The restore algorithm of the image blurred by motion is proposed, and a mathematical model based on motion blur system is eomtrueted£®The Point spread function of the motion blur is given According to the characteristics of blurred images the parameters of point spread function are estimated ,and three methods are introduced for image restoration. The three methods are inverse filtering of image restoration, Lucy-Richardson image restoration and Wiener image restoration. The principles of the three image restoration methods are analyzed. The motion blurred image restoration experiment is made. The results show that the visibility of the image is improved, and the image restoration is more stable.

scholarly journals Determination of the point spread function of layered metamaterials assisted with the blind deconvolution algorithm

2014 ◽  
Vol 47 (1) ◽  
pp. 17-26 ◽  
Author(s):  
David Pastor ◽  
Tomasz Stefaniuk ◽  
Piotr Wróbel ◽  
Carlos J. Zapata-Rodríguez ◽  
Rafał Kotyński
Keyword(s):  
Point Spread Function ◽  
Blind Deconvolution ◽  
Point Spread ◽  
Deconvolution Algorithm ◽  
Spread Function

PERFORMANCE OF BLIND DECONVOLUTION IN OPTOACOUSTIC TOMOGRAPHY

2011 ◽  
Vol 04 (04) ◽  
pp. 385-393 ◽  
Author(s):  
THOMAS JETZFELLNER ◽  
VASILIS NTZIACHRISTOS
Keyword(s):  
Point Spread Function ◽  
Near Infrared ◽  
Blind Deconvolution ◽  
Photoacoustic Imaging ◽  
Reconstructed Image ◽  
Optoacoustic Tomography ◽  
Point Spread ◽  
Spread Function ◽  
Old Mice ◽  
Unknown Point

In this paper, we consider the use of blind deconvolution for optoacoustic (photoacoustic) imaging and investigate the performance of the method as means for increasing the resolution of the reconstructed image beyond the physical restrictions of the system. The method is demonstrated with optoacoustic measurement obtained from six-day-old mice, imaged in the near-infrared using a broadband hydrophone in a circular scanning configuration. We find that estimates of the unknown point spread function, achieved by blind deconvolution, improve the resolution and contrast in the images and show promise for enhancing optoacoustic images.

scholarly journals Blurred Image Restoration with Unknown Point Spread Function

2018 ◽  
Vol 29 (1) ◽  
pp. 189 ◽  
Author(s):  
Ghada Sabah Karam
Keyword(s):  
Image Quality ◽  
Point Spread Function ◽  
Image Quality Assessment ◽  
Blind Deconvolution ◽  
Assessment Method ◽  
Reference Image ◽  
Point Spread ◽  
Spread Function ◽  
Quality Assessment Method ◽  
Blurred Image

Blurring image caused by a number of factors such as de focus, motion, and limited sensor resolution. Most of existing blind deconvolution research concentrates at recovering a single blurring kernel for the entire image. We proposed adaptive blind- non reference image quality assessment method for estimation the blur function (i.e. point spread function PSF) from the image acquired under low-lighting conditions and defocus images using Bayesian Blind Deconvolution. It is based on predicting a sharp version of a blurry inter image and uses the two images to solve a PSF. The estimation down by trial and error experimentation, until an acceptable restored image quality is obtained. Assessments the qualities of images have done through the applications of a set of quality metrics. Our method is fast and produces accurate results.

scholarly journals Application of Blind Deconvolution Algorithm for Deblurring of Saturated Images

2019 ◽  
Vol 8 (2S3) ◽  
pp. 1383-1386
Keyword(s):  
Image Processing ◽  
Image Restoration ◽  
Point Spread Function ◽  
Blind Deconvolution ◽  
Visual Quality ◽  
Visual Examination ◽  
Point Spread ◽  
Spread Function ◽  
Sharp Image ◽  
Deblurring And Denoising

Image Restoration is a field of Image Processing which manages recuperating a unique and sharp image from a debased image utilizing a numerical corruption and reclamation model. This investigation centers around rebuilding of corrupted images which have been obscured by known or obscure debasement work. Image rebuilding which reestablishes an unmistakable image from a solitary haze image is a troublesome issue of assessing two questions: a point spread function (PSF) and its optimal image. Image deblurring can improve visual quality and mitigates movement obscure for dynamic visual examination. We propose a strategy to deblur immersed images for dynamic visual examination by applying obscure piece estimation and deconvolution demonstrating. The haze portion is assessed in a change space, though the deconvolution model is decoupled into deblurring and denoising stages by means of variable part

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