Journal of VLSI Signal Processing 49, 425–442, 2007 * 2007 Springer Science + Business Media, LLC. Manufactured in The United States. DOI: 10.1007/s11265-007-0094-1 Improved Update Step for Scalable Video Coding in Video Surveillance FENGLING LI AND NAM LING Department of Computer Engineering, Santa Clara University, Santa Clara, CA 95053, USA XIAOKANG YANG Institute of Image Communication and Information Processing, Shanghai Jiao Tong University, Shanghai, 200030, China Received: 16 August 2005; Revised: 30 November 2005; Accepted: 14 March 2006 Abstract. Many evolving video services and applications for intelligent security systems require reliable transmission of high quality video to diverse clients over heterogeneous networks using available system resources. Scalable video coding (SVC) is one of the emerging video compression technologies with such potential capabilities. Advances in lifting-based motion-compensated temporal filtering (MCTF) have enabled highly efficient and flexible spatial, temporal, signal-to-noise ratio (SNR), and complexity scalability to be realized over a wide range of bit rates. In this paper, we present an algorithm to improve the update step of MCTF, which serves as an important informative step for the coding performance of SVC. A novel update-step algorithm, which takes advantage of the chrominance information of the video sequence and the correlation of the motion vectors (MVs) of the neighboring blocks as well as the correlation of the derived update MVs in the low-pass frames, is proposed to improve update step of MCTF by (1) computing correct update motion information, (2) generating correct amount of energy contained in the high-pass frames. Experimental results show that the proposed algorithm can significantly improve the quality of the reconstructed video sequence in visual quality. Keywords: scalable video coding (SVC), motion-compensated temporal filtering (MCTF), motion vector (MV) correlation, prediction and update step 1. Introduction Many evolving video services and applications for intelligent security systems require reliable transmis- sion of high quality video to diverse clients over heterogeneous networks using available system resources, particularly in scenarios where the down- stream client capabilities, system resources, and network conditions are not known in advance. One of the emerging technologies to meet such chal- lenges is the scalable video coding (SVC). Recently, SVC is being developed to encode video signal once, but enable decoding from partial streams with respect to the specific rate and resolution required by a certain application [12, 13, 24]. Advances in motion-compensated temporal filtering (MCTF) implemented by a wavelet lifting structure for SVC have enabled highly efficient and flexible spatial, temporal, signal-to-noise ratio (SNR), and complex- ity scalability, with fine granularity, to be realized over a wide range of bit rates [12]. MCTF serves as an important informative step for the coding perfor- mance of SVC. SVC scalability has important applications in intelligent security systems such as video surveillance systems with time-varying chan- nel behaviors and diverse usage characteristics. Digital video surveillance is usually composed of a large number of video sources that are simultaneous-