[CFAR Distinguished Professor Lecture Series]Night Images: Challenges and Solutions from the Perspective of Visibility Enhancement and Object Detection (Hybrid event) by Prof Robby T. Tan
7 Jun 2023 | 11.00am (Singapore Time)
Nighttime conditions are largely associated with low light conditions, which constitute related but different degradation problems, such as low intensity values, high levels of noise (a low signal-to-noise ratio), low contrast, low colour saturation, blurry edges due to noise and low intensity, blur due to motion, etc. Noise is significantly present in low light images because the actual signals emitted by the scene are weak, causing the random noise generated by the camera to dominate the pixel intensity values. In some severe cases, noise levels are higher than the scene pixel intensity, making the recovery intractable. While the low light problem is dominant in nighttime conditions, there are other significant problems.
One of them is the imbalanced distribution of light, particularly when there are man-made lights present. In the areas nearby the light sources, the light can be strong, yet in some distant regions from the sources, the light is considerably weak. The imbalance of light distribution is usually manifested in visual effects like flare, glare and glow. In nighttime conditions, the presence of glow can be prominent, particularly when there are a considerable amount of atmospheric particles, in hazy or foggy scenes. The combination of glow and haze/fog can also degrade the visibility significantly since glow somehow occludes the scene behind.
In this talk, Prof Robby Tan from the National University of Singapore will discuss the challenges in nighttime particularly from the perspective of visibility enhancement and object detection.
SPEAKER
Robby T. Tan is an Associate Professor at Electrical and Computer Engineering (ECE), at the National University of Singapore (NUS). His research is in computer vision and deep learning, particularly in the domains of low level vision (bad weather/nighttime, colour analysis, physics-based vision, optical flow, etc.), human pose/motion analysis, and deep learning’s applications. He received his PhD degree in computer science from the University of Tokyo and was affiliated with Australian National University, Imperial College London, and Utrecht University. He has served as area chair in top conferences like CVPR and ICCV. Currently, he is the area director of the Signal Analysis and Machine Intelligence group at the ECE department, NUS.