Brightness correction and stereovision impression based methods of perceived quality improvement of CCTV video sequences mgr inż. Julian Balcerek, mgr inż. Adam Konieczka, prof. dr hab. inż. Adam Dąbrowski, inż. Mateusz Stankiewicz, inż. Agnieszka Krzykowska Poznań University of Technology, Institute of Control and System Engineering, Division of Signal Processing and Electronic Systems Piotrowo 3a Street, 60-965 Poznań, Poland {julian.balcerek, adam.konieczka, adam.dabrowski}@put.poznan.pl Abstract. In this paper brightness correction and stereovision impression based methods of the perceived quality improvement of CCTV video sequences are presented. These methods are helpful for the monitoring operator in order to evoke attention during a long time observation. Clearness of picture is increased by using local brightness correction method. Another available option is a 3D visualization that can be used, e.g., to observe important image regions, which require an increased attention. Stereovision impression experiments and a real- time 2D to 3D video conversion tool are described. Keywords: CCTV, brightness correction, stereovision, anaglyph, 2D to 3D video conversion 1 Introduction CCTV (closed-circuit television) is a system that is commonly used for surveillance in urban areas that may need monitoring. The resulting job of a monitoring system officer (operator), who must observe the monitor screen for many hours, is quite monotonous and exhausting. In this paper we propose some new image processing tools that can serve as optional aids for the monitoring operator, helping him / her to stay actively conscious for a long time. This is because we offer view diversity and improvement of the perceived quality of images. Two mechanisms are proposed:  increase or decrease of local brightness in order to increase the image clearness and thus the information perception  real-time 2D to 3D conversion in order to increase the subjective informative content of the observed scenes. It has to be stressed that the proposed image transformations are optional, thus they will never burden the monitoring operator. They are helpful in special situations only, e.g., if there is an interesting detail, which requires an increased attention. An experimental software has been prepared for verification of the proposed concepts.