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International Journal on Information and Communication Technology (IJoICT)International Journal on Information and Communication Technology (IJoICT)

Color image enhancement is a vital area in the field of image processing. It is a technique used to enhance the images visual quality. Color enhancement is applied in different applications such as photography, medicine, and computer vision. In this research, eight methods of color enhancement are reviewed according to their methodology, complexity, pros, and cons. Then, three evaluation metrics – Colorfulness (CF), average saturation measure (ASM), and average chroma measure (ACM) – were used to assess each method. The results showed that fuzzy enhancement (FE) exceeded other methods and scored the highest records. This study provides a beneficial resource for researchers involved in image enhancement, as it presents a complete review and detailed analysis of various academic studies published in reputable journals. The work evaluates each study in terms of its findings, proposed algorithm, and accuracy by using many assessment metrics. Furthermore, it emphasizes the strengths and limitations of each method, giving a performance analysis. Additionally, the study discusses future recommendations for improving the effectiveness of these algorithms. Finally, this research is a rich and reliable reference for scholars aiming to develop novel algorithms in this domain.

This research reviewed eight color image enhancement methods, comprehensively discussing each methods mechanism.The study assessed the methods using three evaluation metrics and provided a detailed analysis of their performance.The findings indicate that the Fuzzy Enhancement (FE) method achieved the highest scores, demonstrating its effectiveness.Further research is needed to address the limitations of existing methods and improve the automation and color consistency of color enhancement techniques.

Based on the limitations identified in current color enhancement methods, future research should explore the development of more robust algorithms that can effectively handle varying lighting conditions and image degradation. Specifically, investigating the integration of deep learning techniques with traditional color enhancement methods could lead to improved performance and adaptability. Furthermore, research should focus on creating fully automated color enhancement systems that require minimal user intervention and can consistently deliver high-quality results across diverse image datasets. Finally, exploring the use of perceptual color models and incorporating human visual system characteristics into the enhancement process could lead to more visually pleasing and natural-looking images, ultimately enhancing the user experience and broadening the applicability of these techniques in fields like medical imaging and artistic applications.

  1. Image Color Enhancement Methods: An Experiment-Based Review | International Journal on Information and... doi.org/10.21108/ijoict.v10i2.1044Image Color Enhancement Methods An Experiment Based Review International Journal on Information and doi 10 21108 ijoict v10i2 1044
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