This paper describes the texture representation scheme adopted for MPEG-4 synthetic/natural hybrid coding (SNHC) of texture maps and images. The scheme is based on the concept of multiscale zerotree wavelet entropy (MZTE) coding technique, which provides many levels of scalability layers in terms of either spatial resolutions or picture quality. MZTE, with three different modes (single-Q, multi-Q, and bilevel), provides much improved compression efficiency and fine-gradual scalabilities, which are ideal for hybrid coding of texture maps and natural images. The MZTE scheme is adopted as the baseline technique for the visual texture coding profile in both the MPEG-4 video group and SNHC group. The test results are presented in comparison with those coded by the baseline JPEG scheme for different types of input images. MZTE was also rated as one of the top five schemes in terms of compression efficiency in the JPEG2000 November 1997 evaluation, among 27 submitted proposals.Index Terms-Compression, image and video coding, JPEG-2000, MPEG-4, texture coding, wavelet.
This paper presents a scalable rate control (SRC) scheme based on a more accurate second-order rate-distortion model. A sliding-window method for data selection is used to mitigate the impact of a scene change. The data points for updating a model are adaptively selected such that the statistical behavior is improved. For video object (VO) shape coding, we use an adaptive threshold method to remove shape-coding artifacts for MPEG-4 applications. A dynamic bit allocation among VOs is implemented according to the coding complexities for each VO.SRC achieves more accurate bit allocation with low latency and limited buffer size. In a single framework, SRC offers multiple layers of controls for objects, frames, and macroblocks (MBs). At MB level, SRC provides finer bit rate and buffer control. At multiple VO level, SRC offers superior VO presentation for multimedia applications. The proposed SRC scheme has been adopted as part of the International Standard of the emerging ISO MPEG-4 standard [1], [2].
The Wavelet decomposition algorithm can be used to break down a signal into many components before processing. Single processor based wavelet algorithms have been used in signal and image analysis with great success. However, serial algorithms are inadequate to meet the demand for speed of processing in many real-time applications. An alternative to this problem is to parallelize computing steps in the wavelet computation to meet the real time computing requirements. We have constructed parallel algorithms for wavelet decomposition and reconstruction, and have implemented them in a MasPar parallel computer. Preliminary results indicate a two-order increase in processing speed is achieved.
Abstract| With the success of the Internet and exibility of MPEG-4, transporting MPEG-4 video over the Internet is expected to be an important component of many m ultimedia applications in the near future. Video applications typically have delay and loss requirements, which cannot be adequately supported by the current I n ternet. Thus, it is a challenging problem to design an e cient MPEG-4 video delivery system that can maximize the perceptual quality while achieving high resource utilization. This paper addresses this problem by presenting an end-to-end architecture for transporting MPEG-4 video over the Internet. We present a framework for transporting MPEG-4 video, which includes source rate adaptation, packetization, feedback control, and error control. The main contributions of this paper are: 1 a feedback control algorithm based on Real Time Protocol and Real Time Control Protocol RTP RTCP, 2 an adaptive source encoding algorithm for MPEG-4 video which is able to adjust the output rate of MPEG-4 video to the desired rate, and 3 an e cient and robust packetization algorithm for MPEG video bit-streams at the sync layer for Internet transport. Simulation results show that our end-to-end transport architecture achieves good perceptual picture quality for MPEG-4 video under low bit-rate and varying network conditions and e ciently utilizes network resources.
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