Low-Light Image Enhancement Using Multi-Exposure Sequence Generation And Image Fusion

  • Hrithik Rohilla, Gul Asnani, Kavinder Singh, Anil Singh Parihar

Abstract

Image Enhancement is one of the domains in computer vision with prime importance in real-life applications. Images having poor visual quality and visual defects require enhancement to capture the details in an image. This paper proposes a novel fusion-based method for image enhancement of low light images having non-uniform illumination. The methodology works on the estimation and improvement of the V channel of an image in the HSV model. It estimates several contrast based derivatives of V channel and then fuses them to get the enhanced image with desired features. The proposed approach improves the overall contrast and brightness of images. This approach preserves the details and naturalness of the image. Quantitative and visual analysis of the proposed method validates its performance.

Published
2020-05-15
How to Cite
Hrithik Rohilla, Gul Asnani, Kavinder Singh, Anil Singh Parihar. (2020). Low-Light Image Enhancement Using Multi-Exposure Sequence Generation And Image Fusion. International Journal of Advanced Science and Technology, 29(08), 4481 - 4490. Retrieved from https://sersc.org/journals/index.php/IJAST/article/view/26581
Section
Articles