ABSTRACT
This project explores optimized image enhancement
systems that utilize advanced optimization techniques to improve the quality of
digital images. It discusses various techniques such as histogram equalization,
filtering, edge enhancement, color space conversion, and noise reduction.
Implementation details using Python are provided. Performance evaluation
metrics like PSNR, SSIM, and MSE are employed to assess the effectiveness of
the optimized systems. Practical applications in domains like medical imaging,
surveillance, and multimedia content creation are explored. The project
acknowledges limitations such as subjective image quality assessment and
computational complexity. Overall, it gives insights into optimizing image
quality and its diverse applications
UKAONU, O (2025). Optimized Image Enhancement System:- Ukaonu Precious O. Mouau.afribary.org: Retrieved Apr 05, 2025, from https://repository.mouau.edu.ng/work/view/optimized-image-enhancement-system-ukaonu-precious-o-7-2
ONYINYECHI, UKAONU. "Optimized Image Enhancement System:- Ukaonu Precious O" Mouau.afribary.org. Mouau.afribary.org, 04 Apr. 2025, https://repository.mouau.edu.ng/work/view/optimized-image-enhancement-system-ukaonu-precious-o-7-2. Accessed 05 Apr. 2025.
ONYINYECHI, UKAONU. "Optimized Image Enhancement System:- Ukaonu Precious O". Mouau.afribary.org, Mouau.afribary.org, 04 Apr. 2025. Web. 05 Apr. 2025. < https://repository.mouau.edu.ng/work/view/optimized-image-enhancement-system-ukaonu-precious-o-7-2 >.
ONYINYECHI, UKAONU. "Optimized Image Enhancement System:- Ukaonu Precious O" Mouau.afribary.org (2025). Accessed 05 Apr. 2025. https://repository.mouau.edu.ng/work/view/optimized-image-enhancement-system-ukaonu-precious-o-7-2