Enhancing dynamic videos for surveillance and robotic applications: The robust bilateral and temporal filter

• Published in: Signal processing. Image communication 2014-01, Vol.29 (1), p.80-95
• Main Authors: Maykol Pinto, Andry, Costa, Paulo G., Correia, Miguel V., Paulo Moreira, A.
• Format: Article
• Language: English
• Subjects: Dangerous; Dynamic environment; Dynamics; Filtering; Filtration; Human; Noise; Object recognition; Pixels; Robotic applications; Robust statics; Segmentation; Spatiotemporal filter; Surveillance; Temporal logic; Tracking
• ISSN: 0923-5965; 1879-2677
• DOI: 10.1016/j.image.2013.11.003

Over the last few decades, surveillance applications have been an extremely useful tool to prevent dangerous situations and to identify abnormal activities. Although, the majority of surveillance videos are often subjected to different noises that corrupt structured patterns and fine edges. This makes the image processing methods even more difficult, for instance, object detection, motion segmentation, tracking, identification and recognition of humans. This paper proposes a novel filtering technique named robust bilateral and temporal (RBLT), which resorts to a spatial and temporal evolution of sequences to conduct the filtering process while preserving relevant image information. A pixel value is estimated using a robust combination of spatial characteristics of the pixel's neighborhood and its own temporal evolution. Thus, robust statics concepts and temporal correlation between consecutive images are incorporated together which results in a reliable and configurable filter formulation that makes it possible to reconstruct highly dynamic and degraded image sequences. The filtering is evaluated using qualitative judgments and several assessment metrics, for different Gaussian and Salt–Pepper noise conditions. Extensive experiments considering videos obtained by stationary and non-stationary cameras prove that the proposed technique achieves a good perceptual quality of filtering sequences corrupted with a strong noise component. [Display omitted] •This paper presents a filter technique for dynamic video sequences.•A comparison between the proposed filter and several other filters is made.•Different types of noises (Gaussian and Salt–Pepper) are considered.•The proposed technique is superior in terms of perceptual quality and robustness.