Motion detection and tracking of surveillance videos under distorted environments

There are two aspects of extracting vital visual information such as object identification and detection from continuous surveillance videos. These videos are often distorted by external intrusion factors such as changes in the surrounding lighting conditions, dirt and water on lens and other noisy elements. One of the solutions is to apply image processing algorithms to mitigate these noisy elements for accurate detection and identification. This paper presents a brief review of image or video enhancement algorithms that aims to correct illumination for surveillance videos.