多媒体信号与处理小结(2).ppt
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1、ECTE401 Multimedia Signal Processing,Revision Lecture,Copyright 2008-2012,Christian Ritz,University of Wollongong,1,Revision Lecture,Lecture 1,Described multimedia and multimedia signalsTime and frequencyAnalog and digitalSampling QuantisationUniform,non-uniform,adaptive,Revision Lecture,Copyright 2
2、008-2012,Christian Ritz,University of Wollongong,2,Lecture 2,Define CompressionDescribe lossless and lossy compressionLossless CompressionFixed length binary codeHuffman code Entropy rate,Revision Lecture,Copyright 2008-2012,Christian Ritz,University of Wollongong,3,Lecture 3,Speech signals:Voiced a
3、nd unvoicedShort term correlationLinear predictionRemoves short term correlationModels the vocal tractG721 predictive speech coder32 kbps backward adaptive speech coderEvaluating speech qualityMOS tests,Revision Lecture,Copyright 2008-2012,Christian Ritz,University of Wollongong,4,Lecture 4,Introduc
4、tion to speech coding standardsReview of LP based speech compression modelsExamination of representing the excitation signalReview of current LP based speech coding standards,Revision Lecture,Copyright 2008-2012,Christian Ritz,University of Wollongong,5,Lecture 5,The human auditory systemCD AudioMPE
5、G Audio codingMPEG-1 Layer III(MP3)MPEG-2MPEG-4Dolby Digital AC3Multichannel audio codingMPEG Surround,Revision Lecture,Copyright 2008-2012,Christian Ritz,University of Wollongong,6,Lecture 6,Image RepresentationDigital imagesColour PerceptionVideo representationBasics of Image and Video Coding,Revi
6、sion Lecture,Copyright 2008-2012,Christian Ritz,University of Wollongong,7,Lecture 7,Transforms and image codersWhy transform?Discrete Cosine TransformBaseline JPEG,Revision Lecture,Copyright 2008-2012,Christian Ritz,University of Wollongong,8,Lecture 8,Discrete Wavelet TransformJPEG2000,Revision Le
7、cture,Copyright 2008-2012,Christian Ritz,University of Wollongong,9,Lecture 9,Motivation for video compressionDifferential encodingMotion EstimationMotion Compensation,Revision Lecture,Copyright 2008-2012,Christian Ritz,University of Wollongong,10,Lecture 10,MPEG-1 and MPEG-2 Video Coding:Form frame
8、s into a GOPUse motion estimation and compensationUse JPEG based transformation and quantisationMPEG-2 Video Coding:Provides many more options and bit ratesAllows field based video codingMPEG-4 Video Coding:describes video using a sequence of video objectsUses a hierarchical descriptionEncodes shape
9、s,textural and motion informationAllows scalable encoding and user interactionH.264 Video Coding,Revision Lecture,Copyright 2008-2012,Christian Ritz,University of Wollongong,11,Typical Exam Questions:Speech and Audio Coding,1.is Analysis-by-Synthesis as used in speech coding and what advantage does
10、it provide?See Lecture 4(e.g.slide 14 onwards).What is the purpose of Linear Prediction?Model the short term correlation of the speech signal.See Lecture 3.,Revision Lecture,Copyright 2008-2012,Christian Ritz,University of Wollongong,12,Typical Exam Questions:Speech and Audio Coding,3.Using Huffman
11、coding,find the codewords for the following table of symbols and probabilities.Calculate the entropy of the source and compare with the average codeword length resulting from Huffman coding.Entropy=2.2391Average codeword length=2.33 bits,Revision Lecture,Copyright 2008-2012,Christian Ritz,University
12、 of Wollongong,13,Typical Exam Questions:Speech and Audio Coding,4.List and briefly describe the main steps involved in performing LPC analysisSee Lecture 4Find the mean squared error between the original speech and predicted speechMinimise the mean squared error by setting the derivative to 0Form a
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