DCT-domain spatial transcoding using generalized DCT decimation

[[abstract]]In this paper, we propose a generalized DCT-domain spatial downscaling scheme to improve the visual quality. We analyze the filtering performances and computational complexities of the proposed scheme and the pixel-domain downscaling schemes. The analyses show that the proposed scheme can reduce the aliasing artifact compared to the existing schemes, while the computational complexity may be increased. We also integrate the proposed decimation scheme into the cascaded DCT-domain transcoder for spatial downscaling of a pre-encoded video into its quarter size. Experiments show the proposed approach can achieve better visual quality than the existing schemes.[[fileno]]2030144030019[[department]]電機工程學

On transcoding a B-frame to a P-frame in the compressed domain

2007-2008 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe

Adaptive video delivery using semantics

The diffusion of network appliances such as cellular phones, personal digital assistants and hand-held computers has created the need to personalize the way media content is delivered to the end user. Moreover, recent devices, such as digital radio receivers with graphics displays, and new applications, such as intelligent visual surveillance, require novel forms of video analysis for content adaptation and summarization. To cope with these challenges, we propose an automatic method for the extraction of semantics from video, and we present a framework that exploits these semantics in order to provide adaptive video delivery. First, an algorithm that relies on motion information to extract multiple semantic video objects is proposed. The algorithm operates in two stages. In the first stage, a statistical change detector produces the segmentation of moving objects from the background. This process is robust with regard to camera noise and does not need manual tuning along a sequence or for different sequences. In the second stage, feedbacks between an object partition and a region partition are used to track individual objects along the frames. These interactions allow us to cope with multiple, deformable objects, occlusions, splitting, appearance and disappearance of objects, and complex motion. Subsequently, semantics are used to prioritize visual data in order to improve the performance of adaptive video delivery. The idea behind this approach is to organize the content so that a particular network or device does not inhibit the main content message. Specifically, we propose two new video adaptation strategies. The first strategy combines semantic analysis with a traditional frame-based video encoder. Background simplifications resulting from this approach do not penalize overall quality at low bitrates. The second strategy uses metadata to efficiently encode the main content message. The metadata-based representation of object's shape and motion suffices to convey the meaning and action of a scene when the objects are familiar. The impact of different video adaptation strategies is then quantified with subjective experiments. We ask a panel of human observers to rate the quality of adapted video sequences on a normalized scale. From these results, we further derive an objective quality metric, the semantic peak signal-to-noise ratio (SPSNR), that accounts for different image areas and for their relevance to the observer in order to reflect the focus of attention of the human visual system. At last, we determine the adaptation strategy that provides maximum value for the end user by maximizing the SPSNR for given client resources at the time of delivery. By combining semantic video analysis and adaptive delivery, the solution presented in this dissertation permits the distribution of video in complex media environments and supports a large variety of content-based applications

State-of-the-Art and Trends in Scalable Video Compression with Wavelet Based Approaches

3noScalable Video Coding (SVC) differs form traditional single point approaches mainly because it allows to encode in a unique bit stream several working points corresponding to different quality, picture size and frame rate. This work describes the current state-of-the-art in SVC, focusing on wavelet based motion-compensated approaches (WSVC). It reviews individual components that have been designed to address the problem over the years and how such components are typically combined to achieve meaningful WSVC architectures. Coding schemes which mainly differ from the space-time order in which the wavelet transforms operate are here compared, discussing strengths and weaknesses of the resulting implementations. An evaluation of the achievable coding performances is provided considering the reference architectures studied and developed by ISO/MPEG in its exploration on WSVC. The paper also attempts to draw a list of major differences between wavelet based solutions and the SVC standard jointly targeted by ITU and ISO/MPEG. A major emphasis is devoted to a promising WSVC solution, named STP-tool, which presents architectural similarities with respect to the SVC standard. The paper ends drawing some evolution trends for WSVC systems and giving insights on video coding applications which could benefit by a wavelet based approach.partially_openpartially_openADAMI N; SIGNORONI. A; R. LEONARDIAdami, Nicola; Signoroni, Alberto; Leonardi, Riccard

Efficient compression of motion compensated residuals

EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Layer-based coding, smoothing, and scheduling of low-bit-rate video for teleconferencing over tactical ATM networks

This work investigates issues related to distribution of low bit rate video within the context of a teleconferencing application deployed over a tactical ATM network. The main objective is to develop mechanisms that support transmission of low bit rate video streams as a series of scalable layers that progressively improve quality. The hierarchical nature of the layered video stream is actively exploited along the transmission path from the sender to the recipients to facilitate transmission. A new layered coder design tailored to video teleconferencing in the tactical environment is proposed. Macroblocks selected due to scene motion are layered via subband decomposition using the fast Haar transform. A generalized layering scheme groups the subbands to form an arbitrary number of layers. As a layering scheme suitable for low motion video is unsuitable for static slides, the coder adapts the layering scheme to the video content. A suboptimal rate control mechanism that reduces the kappa dimensional rate distortion problem resulting from the use of multiple quantizers tailored to each layer to a 1 dimensional problem by creating a single rate distortion curve for the coder in terms of a suboptimal set of kappa dimensional quantizer vectors is investigated. Rate control is thus simplified into a table lookup of a codebook containing the suboptimal quantizer vectors. The rate controller is ideal for real time video and limits fluctuations in the bit stream with no corresponding visible fluctuations in perceptual quality. A traffic smoother prior to network entry is developed to increase queuing and scheduler efficiency. Three levels of smoothing are studied: frame, layer, and cell interarrival. Frame level smoothing occurs via rate control at the application. Interleaving and cell interarrival smoothing are accomplished using a leaky bucket mechanism inserted prior to the adaptation layer or within the adaptation layerhttp://www.archive.org/details/layerbasedcoding00parkLieutenant Commander, United States NavyApproved for public release; distribution is unlimited

Wavelets and Subband Coding

First published in 1995, Wavelets and Subband Coding offered a unified view of the exciting field of wavelets and their discrete-time cousins, filter banks, or subband coding. The book developed the theory in both continuous and discrete time, and presented important applications. During the past decade, it filled a useful need in explaining a new view of signal processing based on flexible time-frequency analysis and its applications. Since 2007, the authors now retain the copyright and allow open access to the book

Language and compiler support for stream programs

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2009.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Includes bibliographical references (p. 153-166).Stream programs represent an important class of high-performance computations. Defined by their regular processing of sequences of data, stream programs appear most commonly in the context of audio, video, and digital signal processing, though also in networking, encryption, and other areas. Stream programs can be naturally represented as a graph of independent actors that communicate explicitly over data channels. In this work we focus on programs where the input and output rates of actors are known at compile time, enabling aggressive transformations by the compiler; this model is known as synchronous dataflow. We develop a new programming language, StreamIt, that empowers both programmers and compiler writers to leverage the unique properties of the streaming domain. StreamIt offers several new abstractions, including hierarchical single-input single-output streams, composable primitives for data reordering, and a mechanism called teleport messaging that enables precise event handling in a distributed environment. We demonstrate the feasibility of developing applications in StreamIt via a detailed characterization of our 34,000-line benchmark suite, which spans from MPEG-2 encoding/decoding to GMTI radar processing. We also present a novel dynamic analysis for migrating legacy C programs into a streaming representation. The central premise of stream programming is that it enables the compiler to perform powerful optimizations. We support this premise by presenting a suite of new transformations. We describe the first translation of stream programs into the compressed domain, enabling programs written for uncompressed data formats to automatically operate directly on compressed data formats (based on LZ77). This technique offers a median speedup of 15x on common video editing operations.(cont.) We also review other optimizations developed in the StreamIt group, including automatic parallelization (offering an 11x mean speedup on the 16-core Raw machine), optimization of linear computations (offering a 5.5x average speedup on a Pentium 4), and cache-aware scheduling (offering a 3.5x mean speedup on a StrongARM 1100). While these transformations are beyond the reach of compilers for traditional languages such as C, they become tractable given the abundant parallelism and regular communication patterns exposed by the stream programming model.by William Thies.Ph.D