Sabir Muhammad Farooq, Heath Robert W, Bovik Alan Conrad
K-WILL Corporation, San Jose, CA 95134, USA.
IEEE Trans Image Process. 2009 Jan;18(1):90-105. doi: 10.1109/TIP.2008.2005819.
Multimedia communication has become one of the main applications in commercial wireless systems. Multimedia sources, mainly consisting of digital images and videos, have high bandwidth requirements. Since bandwidth is a valuable resource, it is important that its use should be optimized for image and video communication. Therefore, interest in developing new joint source-channel coding (JSCC) methods for image and video communication is increasing. Design of any JSCC scheme requires an estimate of the distortion at different source coding rates and under different channel conditions. The common approach to obtain this estimate is via simulations or operational rate-distortion curves. These approaches, however, are computationally intensive and, hence, not feasible for real-time coding and transmission applications. A more feasible approach to estimate distortion is to develop models that predict distortion at different source coding rates and under different channel conditions. Based on this idea, we present a distortion model for estimating the distortion due to quantization and channel errors in MPEG-4 compressed video streams at different source coding rates and channel bit error rates. This model takes into account important aspects of video compression such as transform coding, motion compensation, and variable length coding. Results show that our model estimates distortion within 1.5 dB of actual simulation values in terms of peak-signal-to-noise ratio.
多媒体通信已成为商业无线系统中的主要应用之一。主要由数字图像和视频组成的多媒体源具有很高的带宽要求。由于带宽是一种宝贵的资源,因此针对图像和视频通信优化其使用非常重要。因此,开发用于图像和视频通信的新型联合信源信道编码(JSCC)方法的兴趣与日俱增。任何JSCC方案的设计都需要估计在不同信源编码率和不同信道条件下的失真。获得此估计的常用方法是通过仿真或操作率失真曲线。然而,这些方法计算量很大,因此对于实时编码和传输应用来说并不可行。一种更可行的估计失真的方法是开发能够预测在不同信源编码率和不同信道条件下失真的模型。基于这一想法,我们提出了一种失真模型,用于估计在不同信源编码率和信道误码率下MPEG-4压缩视频流中由于量化和信道错误导致的失真。该模型考虑了视频压缩的重要方面,如变换编码、运动补偿和可变长度编码。结果表明,就峰值信噪比而言,我们的模型估计的失真与实际仿真值相差在1.5 dB以内。