Single image dehazing using cycle consistent adversarial networks

• Main Authors: Tzu-YuHuang, 黃子育
• Other Authors: Shen-Chuan Tai
• Format: Others
• Language: en_US
• Published: 2019
• Online Access: http://ndltd.ncl.edu.tw/handle/2cu68b

碩士 === 國立成功大學 === 電腦與通信工程研究所 === 107 === Computer vision is widely used in many fields, such as surveillance system, image recognition, etc. However, image quality highly affects the result and accuracy in image recognition. Images that taken at outdoor are highly affected by particles in air. Particles cause light scattering, so the images become hazy. Hazy images will highly decrease the image quality. It is not conducive to image recognition and it will decrease the accuracy. In recent years, many researchers proposed many single image dehazing methods aim to solve the problem. In this Thesis, a method based on cycle consistent adversarial networks is proposed. After adding the dark channel, depth map and other losses into the networks, our experiment has a better result both in visual and quantitative metrics.