Single Image Depth Level Estimation Using Dark Channel Prior

2018 2nd International Conference on Artificial Intelligence Applications and Technologies

计算机科学

Cao, Yichao^1,2 ; Lu, Xiaobo^1,2

School of Automation, Southeast University, Nanjing

210096, China^1

Key Laboratory of Measurement and Control of Complex Systems of Engineering, Ministry of Education, Southeast University, Nanjing

210096, China^2

关键词: Dark channel priors;    Depth information;    Estimation algorithm;    Histogram analysis;    Multi-threshold segmentation;    Prior knowledge;    Smoke detection;    Video analysis;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/435/1/012036/pdf
DOI  :  10.1088/1757-899X/435/1/012036

学科分类：计算机科学（综合）

来源: IOP

【 摘 要 】

In this paper, we present a simple image depth level estimation algorithm. From the dark channel prior theory, an estimate of the air transmittance in the image is calculated. In wild surveillance, the disparity in the image poses a huge challenge for smoke detection and other video analysis tasks. Appropriate depth level estimation provide significant prior knowledge for subsequent identification and detection. For landscape images, we can approximate the air transmittance to depth information for histogram analysis. The depth value is segmented by a multi-threshold segmentation algorithm, and the resulting image can be used for forest fireworks detection and the like. This method does not rely on samples and classifiers, and the algorithm does not require training. The final experimental results show that the depth level estimation of a single landscape image based on the dark channel prior can achieve good results.