학술논문

Removal of Rain Streaks in Air Using GAN
Document Type
Conference
Source
2021 4th International Conference on Artificial Intelligence and Big Data (ICAIBD) Artificial Intelligence and Big Data (ICAIBD), 2021 4th International Conference on. :589-593 May, 2021
Subject
Computing and Processing
Image quality
Rain
Quantization (signal)
Target recognition
Image color analysis
Object detection
Big Data
rainstreak removal
generative adversarial network
quantilization
YUV conversion
Language
Abstract
Rain streaks in the air can be harmful for the image quality, which makes photograph blur and unaesthetic. Pictures with rain streaks are also bad resource for target detection and recognition. Therefore, we promote a method to remove rain streaks based on generative adversarial networks. We find that the rain streaks exit mainly in high-frequency component of a picture. Therefore, our work focuses on the part contains the rain streaks and avoid affecting details and color information of the picture. We also introduced a quantization method to improve network to make it thinner. Based on experiment, rains in the picture are removed effectively. Images after processing are cleaner than the original ones.