Adaptive complex illumination image enhancement algorithm based on Retinex

Yifei Bao; Zongmiao Dai; Peizhang Wu

doi:10.1117/12.3055349

12 December 2024 Adaptive complex illumination image enhancement algorithm based on Retinex

Yifei Bao, Zongmiao Dai, Peizhang Wu

Author Affiliations +

Proceedings Volume 13439, Fourth International Conference on Testing Technology and Automation Engineering (TTAE 2024); 134392J (2024) https://doi.org/10.1117/12.3055349
Event: Fourth International Conference on Testing Technology and Automation Engineering (TTAE 2024), 2024, Xiamen, China

Abstract

With the expansion of head-mounted displays into various professional domains, there is an increasing demand for adaptive complex illumination image enhancement algorithms that are computationally efficient and resource-conservative. This study introduces a method to categorize input images into high-light, normal, and low-light images based on brightness thresholds. Enhanced Retinex-based algorithms are proposed to process these categories. For low-light images, operations such as histogram equalization and sharpening are applied to enhance the details of the illumination component. For highlight images, an illumination component estimation method is utilized to effectively reduce noise and enhance contour information, followed by normalization using a sigmoid function. The effectiveness of the low-light enhancement algorithm is validated using the LOL dataset. The high-light enhancement algorithm is validated using a self-constructed dataset.

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

Citation Download Citation

Yifei Bao, Zongmiao Dai, and Peizhang Wu "Adaptive complex illumination image enhancement algorithm based on Retinex", Proc. SPIE 13439, Fourth International Conference on Testing Technology and Automation Engineering (TTAE 2024), 134392J (12 December 2024); https://doi.org/10.1117/12.3055349

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