A Review on Frame Indexing and Labeling in Dynamic Rainy Video Scenes with Rain Pixel Recovery - Punam P, Kansare; Meshram, Ashwini (International Journal of Computer Sciences and Engineering, 2014)
Rain act as a noise that affect videos and images. Mostly, noises are observed due to weather conditions that will affect audio correspondence, object recognition, motion segmentation, and object tracking. While editing movie or any security surveillance if any problem is found due to rain constraints the object cannot be tracked well. Rain drops are spatially distributed which falls at very high velocities. Hence, it leads to produce sharp intensity variations in an image where each drop refracts and reflects the environment. Such group of falling rain drops generates a complex time varying signal in both images as well as in videos. Random rain pixel detection and noise filtrations lead to achieve the high performance in dynamic videos having various vision-based applications. So, by extracting the key frames from the large size video we can compress it to smaller one which helps to retrieve dynamic frame through indexing and labeling. After the key frame selection rain pixel recovery algorithm will provide the compressed video with the rain pixel recovery from highly dynamic scenes.