TY  - JOUR
T1  - A Survey on Various Image Deblurring Methods
AU - Hamood, Sabah Fadhel AU - Rahim, Mohd Shafry Mohd AU - Farook, Omar AU - Kasmuni, Daud 
JO  - Journal of Engineering and Applied Sciences
VL  - 11
IS  - 3
SP  - 561
EP  - 569
PY  - 2016
DA  - 2001/08/19
SN  - 1816-949x
DO  - jeasci.2016.561.569
UR  - https://makhillpublications.co/view-article.php?doi=jeasci.2016.561.569
KW  - Blur
KW  -deblur
KW  -deconvolution
KW  -degradation
KW  -PSF
KW  -Gaussian
KW  -Latent
KW  -outliers
AB  - Image blur is one of the main types of degradation that reduces image quality. Image deblurring is
an attempt to invert blurring process by using mathematical model to get best estimation of latent (sharp) image.
Blurring can be modeled mathematically as a convolution process between two functions which are image and
Point Spread Function (PSF). PSF can be classified into more than one type depending on the reason for
blurring. Gaussian is the type of PSF this study will focus on, and an implementation of such PSF to compare
different deblurring methods. Based on the availability of prior knowledge about the degradation kernel (PSF),
the deblurring methods can be divided into two major categories which are non-blind deconvolution
and blind-deconvolution. Peak Signal to Noise Ratio (PSNR) and Structural Similarity (SSIM) are the tools used
to estimate the performance of these methods.
ER  -