Improve image de-blurring

Abbadi, Nidhal El; Taee, Elaf J. Al; Abdulsamad, Zainalabideen

doi:10.1109/itce.2018.8316595

Cited by 3 publications

(3 citation statements)

References 2 publications

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“… Still in the laboratory research stage. ★★★★ Markov random field method Abbadi et al [ 45 ] Markov basis with Laplace filter Used for color and gray images deblurring. Cannot solve deep blur estimation.…”

Section: Edge Prediction Methodsmentioning

confidence: 99%

“…Moreover, Abbadi et al also proposed a filter method based on combining Markov basis and Laplace filter. It is slightly modified to make it appropriate for color images and solved the escalation image edge content [ 45 ]. A framework of Markov Random Field (MRF) was formulated to solve for the depth map by exploiting both stereo cues and motion blur cues.…”

Section: Development Of Image Motion Deblurring Techniquesmentioning

confidence: 99%

See 1 more Smart Citation

A state-of-the-art review of image motion deblurring techniques in precision agriculture

Chen

2023

Heliyon

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Section: Edge Prediction Methodsmentioning

confidence: 99%

Section: Development Of Image Motion Deblurring Techniquesmentioning

confidence: 99%

A state-of-the-art review of image motion deblurring techniques in precision agriculture

Chen

2023

Heliyon

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“…Besides, the deblurring performance for both color and gray images is increased by using a median filter. This work has a good enhancement for image deblurring compared with other techniques [21]. Shah & Dalal presented a blind motion deblurring algorithm, which determines the motion blur parameters (length, angle) in a transformed cepstrum domain by a blind no-Reference Image Spatial Quality Evaluator (BRISQUE) employed to tuning PSF parameters.…”

Section: Literature Reviewmentioning

confidence: 99%

A Survey on Blind De-Blurring of Digital Image

Abdulkhaleq

Abbadi

Hassani

2022

eijs

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Nowadays, huge digital images are used and transferred via the Internet. It has been the primary source of information in several domains in recent years. Blur image is one of the most common difficult challenges in image processing, which is caused via object movement or a camera shake. De-blurring is the main process to restore the sharp original image, so many techniques have been proposed, and a large number of research papers have been published to remove blurring from the image. This paper presented a review for the recent papers related to de-blurring published in the recent years (2017-2020). This paper focused on discussing various strategies related to enhancing the software's for image de-blur. The aim of this research is to help researchers to understand the current algorithms and techniques in this field, and eventually may developing new and more efficient algorithms for enhancing blurred images.

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