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020			_aTHE0010207 (Local) _qHardback
040			_aUMPSA _beng _cUMPSA _erda
090			_aFTKPM .Q74 2025 r Thesis
100	0		_aSyafiq Qhushairy Bin Syamsul Amri, _eauthor.
245	1	0	_aUnderwater image enhancement using integrated chromatic adaptation modified white balance / _cSyafiq Qhushairy Bin Syamsul Amri
264		1	_aKuantan, Pahang : _bUMPSA, _c2025
264		4	_c© 2025
300			_axiv, 125 pages : _billustrations (some color) ; _c30 cm. + _e1 CD-COM
336			_2rdacontent _atext
337			_2rdamedia _aunmediated
338			_2rdacarrier _avolume
347			_2rda _atext file _bPDF
500			_aFaculty of Manufacturing and Mechatronic Engineering Technology
502			_aThesis (Master of Science) -- Universiti Malaysia Pahang – 2025
504			_aIncludes bibliographical references
520	3		_aUnderwater image enhancement is crucial for improving visual perception and the applicability of underwater images. Various methods have been proposed to enhance underwater images, such as modeling image enhancement as a distortion process and utilizing color constancy-based schemes. Challenges in underwater image processing include factors like turbidity, light refraction, and low-contrast objects, which impact image quality and cause unnatural views and disrupted object colors in the underwater environment. The objective in this thesis is to develop robust image processing algorithms that can effectively enhance underwater images and improve visibility for various applications. This will help researchers and professionals in fields such as marine biology and underwater photography to obtain detail and improve visibility images of underwater scenes. The second objective is to analyse and verify the developed algorithm for improvement of images color cast and object details, ultimately leading to image quality. The method suggested in this thesis is the Integrated Chromatic Adaptation Modified White Balance (CAMWB), which aims to enhance visibility and object detail in underwater images. This work focuses on addressing the primary difficulties of visibility and object detail in the underwater environment, as the existing methods still require assistance in effectively resolving these issues. This work has developed algorithms based on mathematical equations, leading to the creation of a novel three-stage CAMWB technique. In the first stage, the modification process using chromatic adaptation-based image color channel neutralization is implemented to improve and correct the color balance of the underwater image. The second stage is image intensity mapping on a dual image histogram, which is used to improve the performance of the less effective color channels. Lastly, brightness reconstruction for each color channel is used in the last stage to enhance the overall object color and achieve a more realistic representation of the underwater scene by adjusting the contrast and shadows. The findings indicate that the CAMWB implementation method effectively resolved particular problems related to visibility, object color cast, and image details. Additionally, it enhanced the overall quality of underwater images by enhancing uniform illumination and image contrast. The proposed approach demonstrates superior performance in extracting information from underwater images. Experiments conducted on 300 sample underwater images taken from Redang Island in various scenarios demonstrate that the proposed CAMWB method enhances the visual quality of output images and surpasses existing state-of-the-art methods such as integrated color model (ICM), the natural-based underwater image color enhancement through the fusion of swarm intelligence algorithm (NUCE), the dual-intensity images and Rayleigh stretching (DIRS), the bio-inspired multi-exposure fusion framework for low light image enhancement (BIMEF), the Rayleigh contrast-limited adaptive histogram equalisation (Rayleigh CLAHE), the Histogram Equalisation (HE), and the color balance and fusion for underwater image enhancement (WB Multiscale Fusion). The results indicate that CAMWB outperforms other methods in terms of average gradient value, with a value of 9.201. In conclusion, the Integrated Chromatic Adaptation Modified White Balance (CAMWB) algorithm developed in this study significantly improves underwater image quality by addressing critical challenges such as reduced water clarity, light attenuation, and color distortion.
610	2	0	_aFaculty of Manufacturing and Mechatronic Engineering Technology _xDissertations
650		0	_aUniversities and colleges _xDissertations
650		0	_aTheses _xDissertations
942			_2lcc _cTHESIS
999			_c103825 _d103831