A survey on various image deblurring methods
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 w...
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| Format: | Article |
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Medwell Journals
2016
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| _version_ | 1796861736940208128 |
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| author | Hamood, Sabah Fadhel Mohd. Rahim, Mohd. Shafry Farook, Omar Kasmuni, Daud |
| author_facet | Hamood, Sabah Fadhel Mohd. Rahim, Mohd. Shafry Farook, Omar Kasmuni, Daud |
| author_sort | Hamood, Sabah Fadhel |
| collection | ePrints |
| description | 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. |
| first_indexed | 2024-03-05T20:00:56Z |
| format | Article |
| id | utm.eprints-71227 |
| institution | Universiti Teknologi Malaysia - ePrints |
| last_indexed | 2024-03-05T20:00:56Z |
| publishDate | 2016 |
| publisher | Medwell Journals |
| record_format | dspace |
| spelling | utm.eprints-712272017-11-15T03:52:21Z http://eprints.utm.my/71227/ A survey on various image deblurring methods Hamood, Sabah Fadhel Mohd. Rahim, Mohd. Shafry Farook, Omar Kasmuni, Daud QA75 Electronic computers. Computer science 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. Medwell Journals 2016 Article PeerReviewed Hamood, Sabah Fadhel and Mohd. Rahim, Mohd. Shafry and Farook, Omar and Kasmuni, Daud (2016) A survey on various image deblurring methods. Journal of Engineering and Applied Sciences, 11 (3). pp. 561-569. ISSN 1816-949X https://www.scopus.com/inward/record.uri?eid=2-s2.0-85013643470&partnerID=40&md5=480414dc459ab7d98e0bfe6bf3a9a880 |
| spellingShingle | QA75 Electronic computers. Computer science Hamood, Sabah Fadhel Mohd. Rahim, Mohd. Shafry Farook, Omar Kasmuni, Daud A survey on various image deblurring methods |
| title | A survey on various image deblurring methods |
| title_full | A survey on various image deblurring methods |
| title_fullStr | A survey on various image deblurring methods |
| title_full_unstemmed | A survey on various image deblurring methods |
| title_short | A survey on various image deblurring methods |
| title_sort | survey on various image deblurring methods |
| topic | QA75 Electronic computers. Computer science |
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