Low-light image enhancement algorithm based on an atmospheric physical model
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Low-light image enhancement algorithm based on an atmospheric physical model Xiaomei Feng1,2 · Jinjiang Li1,2
· Zhen Hua1
Received: 25 March 2020 / Revised: 27 July 2020 / Accepted: 6 August 2020 / © Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract Under low illumination, the colour constancy of human vision can be used for correctly determining the colour of objects according to the fixed reflection coefficient of external light and objects. However, video image acquisition equipment does not implement the colour constancy characteristic of the human visual system. Under low illumination, only a small amount of light is reflected from the surface of the imaged object; as a result, the captured image is underexposed. After statistical analysis of low-light images, these inverted underexposed images appear foggy. Inversion is a uniform and reversible operation that is performed on the entire image. Hereby, a method is proposed for resolving low-light images using conventional physical models. First, a low-light image is inverted for obtaining a foggy image. Subsequently, a pyramid-type dense residual block network and a dark channel prior K-means classification method are applied to the foggy image, to calculate the transmission and atmospheric light. Finally, the parameters obtained from this solution are incorporated into the low-light imaging model to obtain a clear image. We subjectively and qualitatively analysed the experimental results, and used information entropy and average gradient for objective quantitative analysis. We demonstrate that the algorithm improves the overall brightness and contrast of the imaged scenes, and the obtained enhanced images are clear and natural. Keywords Low-light image · Low-light enhancement · Low-light imaging model
Jinjiang Li
[email protected] Xiaomei Feng [email protected] Zhen Hua [email protected] 1
School of Information and Electronic Engineering, Shandong Technology and Business University, Yantai 264005, China
2
Co-innovation Center of Shandong Colleges and Universities: Future Intelligent Computing, Yantai 264005, China
Multimedia Tools and Applications
1 Introduction With the development of science and technology, it has become possible to record the splendour of the world in the form of images, using digital imaging equipment. Because capturing high-quality images in dim light is difficult, an angle with sufficient light is typically chosen for shooting images. Under nocturnal illumination, insufficient indoor lighting, or cloudy weather conditions [12], the photon count and signal to noise ratio (SNR) are low. As a result, the amount of light that is reflected from the surface of the imaged object is relatively small, and the image acquisition equipment cannot effectively record the colours of the imaged object [10]. Images captured in low light have low brightness, low contrast, relatively high noise, and artifacts, which seriously affect the visual experience. When the light source changes, the reflection spect
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