Zobrazeno 1 - 10
of 14
pro vyhledávání: '"Hazique Aetesam"'
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 8543-8558 (2024)
In this article, we propose a variational approach for estimating the clean hyperspectral images (HSI) that are corrupted by the combined effect of Gaussian noise, impulse noise, stripes, and deadlines. Successful removal of noise from the corrupted
Externí odkaz:
https://doaj.org/article/f63f9cc081db42cba1a8e911386eb0ad
Publikováno v:
IEEE Access, Vol 9, Pp 169335-169347 (2021)
Hyperspectral images (HSI) are corrupted by a combination of Gaussian and impulse noise. Successful denoising of HSI data increases the accuracy of high-level vision operations like classification, target tracking and land-cover problem. On the one h
Externí odkaz:
https://doaj.org/article/ebce0581afb14458beeead7da1fd3099
Autor:
Hazique Aetesam, Suman Kumar Maji
Publikováno v:
Remote Sensing Letters. 13:767-777
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::10990497ed8838b65ecf67ae52e39ca5
https://doi.org/10.1080/2150704x.2022.2077152
https://doi.org/10.1080/2150704x.2022.2077152
Publikováno v:
Advances in Computational Intelligence and Robotics ISBN: 9781799888925
Image denoising is a class of image processing algorithms that aim to enhance the visual quality of the acquired images by removing noise inherent in them and is an active area of research under image enhancement and reconstruction techniques. Tradit
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b8a571e9e3d7534249b22a927170098e
https://doi.org/10.4018/978-1-7998-8892-5.ch011
https://doi.org/10.4018/978-1-7998-8892-5.ch011
Publikováno v:
Advances in Computational Intelligence and Robotics ISBN: 9781799888925
Remote sensing technologies such as hyperspectral imaging (HSI) and medical imaging techniques such as magnetic resonance imaging (MRI) form the pillars of human advancement. However, external factors like noise pose limitations on the accurate funct
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a4afe69ba562f3e924125949572d33b7
https://doi.org/10.4018/978-1-7998-8892-5.ch020
https://doi.org/10.4018/978-1-7998-8892-5.ch020
Publikováno v:
IET Image Processing. 14:3366-3372
The authors present a proximal approach to hyperspectral image denoising adapted to the mixed noise behaviour of hyperspectral data; named hyperspectral image proximal denoiser (HSIProxDenoiser). A combination of Gaussian-impulse noise has been handl
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::027de421983909b09d4968ecbbf92426
https://doi.org/10.1049/iet-ipr.2019.1763
https://doi.org/10.1049/iet-ipr.2019.1763
Autor:
Hazique Aetesam, Suman Kumar Maji
Publikováno v:
Journal of digital imaging.
Image denoising is an important preprocessing step in low-level vision problems involving biomedical images. Noise removal techniques can greatly benefit raw corrupted magnetic resonance images (MRI). It has been discovered that the MR data is corrup
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7f0bce03993dfc1e0113334e7cd186ec
https://pubmed.ncbi.nlm.nih.gov/36474088
https://pubmed.ncbi.nlm.nih.gov/36474088
Publikováno v:
Communications in Computer and Information Science ISBN: 9783031113482
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::15bc48e47c76df9ffe92150c1b561f94
https://doi.org/10.1007/978-3-031-11349-9_14
https://doi.org/10.1007/978-3-031-11349-9_14
Autor:
Hazique Aetesam, Suman Kumar Maji
Publikováno v:
2020 7th International Conference on Signal Processing and Integrated Networks (SPIN).
In this paper, we formulate a variational framework for the deconvolution of ultrasound images obtained from pulsed-echo linear array transducers. These images, obtained as a result of acoustic response of soft-biological tissues are called Tissue Re
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e1d9711a565b71db8d9a794596d4a40d
https://doi.org/10.1109/spin48934.2020.9071028
https://doi.org/10.1109/spin48934.2020.9071028
Autor:
Hazique Aetesam, Suman Kumar Maji
Publikováno v:
2020 International Conference on Contemporary Computing and Applications (IC3A).
In this paper, we design an optimization problem for denoising 3 dimensional Magnetic Resonance Image (MRI) data. The problem is formulated as a variational technique considering the underlying distribution of noise to be Gaussian and Laplacian. We p
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9fdba6e8df3678cfb24dbf568e0c108f
https://doi.org/10.1109/ic3a48958.2020.233285
https://doi.org/10.1109/ic3a48958.2020.233285