A perceptual-based video coder for error resilience

Abstract

Summary form only given. Error resilience is an important requirement when errors occur during video transmission. The video transmitted over the Internet is usually a packetized stream and thus the common errors for the Internet video are due to packet loss, caused by buffer overflows in routers, late arrival of packets, and bit errors in the network. This loss results in single or multiple macroblock losses in the decoding process and causes severe degradation in perceived quality and error propagation. We present a perceptual preprocessor based on the insensitivity of the human visual system to the mild changes in pixel intensity in order to segment video into regions according to perceptibility of picture changes. With the information of segmentation, we determine which macroblocks require motion estimation and then which macroblocks need to be included in the second layer. The second layer contains the coarse (less quantized) version of the most perceptually-critical picture information to provide redundancy used to reconstruct lost coding blocks. This information is transmitted in a separate packet, which provides path and time diversities when packet losses are uncorrelated. This combination of methods provides a significant improvement in received quality when losses occur, without significantly degrading the video in a low-bit-rate video channel. Our proposed scheme is easily scalable to various data bitrates, picture quality, and computational complexity for use on different platforms. Because the data in our layered video stream is standards-compliant, our proposed schemes require no extra non-standard device to encode/decode the video and they are easily integrated into the current video standards such as H.261/263, MPEG1/MPEG2 and the forthcoming MPEG4.