An image enhancement algorithm based on multi-scale Retinex theory to improve the images quality of sensors

Yiyao Li; Zhong Chen; Wenyuan Sun

doi:10.1117/12.3000520

7 March 2024 An image enhancement algorithm based on multi-scale Retinex theory to improve the images quality of sensors

Yiyao Li, Zhong Chen, Wenyuan Sun

Author Affiliations +

Proceedings Volume 13086, MIPPR 2023: Pattern Recognition and Computer Vision; 130860J (2024) https://doi.org/10.1117/12.3000520
Event: Twelfth International Symposium on Multispectral Image Processing and Pattern Recognition (MIPPR2023), 2023, Wuhan, China

Abstract

Nowadays, image recognition plays a pivotal role in acquiring data via sensors. However, the adaptability of traditional algorithms is hindered by the unpredictable nature of open environments, varying sensor quality, and image dimensions. Challenges arise in adverse conditions like inclement weather, low light, and optical distortions. Retinex-based methods have emerged as a viable solution, effectively enhancing images plagued by shadows or poor lighting. Yet, issues surface when images possess saturated colors; the conventional multi-scale Retinex with color restoration risks color inversion. Moreover, during gain compensation, extreme histogram values occupy significant gray level space, obscuring vital image details. This study delves into these challenges and proposes an enhanced multi-scale Retinex algorithm. Our approach substitutes logarithmic functions with tansig functions, eliminating color inversion risks. Additionally, a novel gain compensation method, integrating histogram stretching with Gamma correction, refines image clarity. The algorithm's robustness is evidenced in diverse scenarios, including adverse weather, low light, underwater imaging, and non-uniform lighting. Experimental results validate our method's superiority, surpassing other Retinex-based techniques both qualitatively and quantitatively. This research contributes valuable insights into image enhancement methodologies, fostering advancements in sensor-based data gathering in Smart Spaces.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Yiyao Li, Zhong Chen, and Wenyuan Sun "An image enhancement algorithm based on multi-scale Retinex theory to improve the images quality of sensors", Proc. SPIE 13086, MIPPR 2023: Pattern Recognition and Computer Vision, 130860J (7 March 2024); https://doi.org/10.1117/12.3000520

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KEYWORDS

Image enhancement

Image quality

Image sensors

Algorithms

Detection and tracking algorithms

Adverse weather

Distortion

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