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UCSB ECE 160 - Video Compression

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ECE160 Spring 2011 Lecture 13 Video Compression Techniques 1 ECE160 Multimedia Lecture 13: Spring 2011 Video Compression Techniques MPEG-4, MPEG-7 and BeyondECE160 Spring 2011 Lecture 13 Video Compression Techniques 2 Overview of MPEG-4 • MPEG-2 is designed for HDTV, i.e. moving photography • MPEG-4: a newer standard designed for computer generated multimedia. Besides compression, it pays greater attention to issues about user interaction. • MPEG-4 departs from its predecessors in adopting a new object-based coding. The next slide illustrates how MPEG-4 videos can be composed and manipulated by simple operations on the visual objects. • Offering higher compression ratios is also beneficial for digital video composition, manipulation, indexing, and retrieval. • The bit-rate for MPEG-4 video now covers a large range between 5 kbps to 10 Mbps.ECE160 Spring 2011 Lecture 13 Video Compression Techniques 3 Composition and Manipulation of MPEG-4 Videos BIFS Binary Format for Scenes (extension of VRML Virtual Reality Modeling Language)ECE160 Spring 2011 Lecture 13 Video Compression Techniques 4 MPEG-4 • MPEG-4 is an entirely new standard for: (a) Composing media objects to create desirable audiovisual scenes. • (b) Multiplexing and synchronizing the bitstreams for these media data entities so that they can be transmitted with guaranteed Quality of Service (QoS). • (c) Interacting with the audiovisual scene at the receiving end - provides a toolbox of advanced coding modules and algorithms for audio and video compressions.ECE160 Spring 2011 Lecture 13 Video Compression Techniques 5 MPEG-1 and MPEG-2 Interaction is outside the standardECE160 Spring 2011 Lecture 13 Video Compression Techniques 6 MPEG-4ECE160 Spring 2011 Lecture 13 Video Compression Techniques 7 Overview of MPEG-4 • Video Object Oriented Hierarchical Description of a Scene in MPEG-4 Visual Bitstreams. – The hierarchical structure of MPEG-4 visual bitstreams is very different from MPEG-1 and -2, It is very much video object-oriented.ECE160 Spring 2011 Lecture 13 Video Compression Techniques 8 Overview of MPEG-4 • Video-object Sequence (VS) - delivers the complete MPEG-4 visual scene, which may contain 2-D or 3-D natural or synthetic objects. • Video Object (VO) - a particular object in the scene, which can be of arbitrary (non-rectangular) shape corresponding to an object or background of the scene. • Video Object Layer (VOL) - facilitates a way to support (multi-layered) scalable coding. A VO can have multiple VOLs under scalable coding, or have a single VOL under non-scalable coding. • Group of Video Object Planes (GOV) - groups Video Object Planes together (optional level). • Video Object Plane (VOP) - a snapshot of a VO at a particular moment.ECE160 Spring 2011 Lecture 13 Video Compression Techniques 9 VOP-based vs. Frame-based Coding • MPEG-1 and -2 do not support the VOP concept, and hence their coding method is referred to as frame-based (also known as Block-based coding).ECE160 Spring 2011 Lecture 13 Video Compression Techniques 10 VOP-based vs. Frame-based Coding A possible example in which two potential matches yield small errors for block-based coding. Each VOP is of arbitrary shape and will obtain a unique motion vector consistent with the actual object motion.ECE160 Spring 2011 Lecture 13 Video Compression Techniques 11 VOP-based Coding • MPEG-4 VOP-based coding also employs the Motion Compensation technique: – An Intra-frame coded VOP is called an I-VOP. – The Inter-frame coded VOPs are called P-VOPs if only forward prediction is employed, or B-VOPs if bi-directional predictions are employed. • The new difficulty for VOPs: may have arbitrary shapes, shape information must be coded in addition to the texture of the VOP. Note: texture here actually refers to the visual content, that is the gray-level (or chroma) values of the pixels in the VOP.ECE160 Spring 2011 Lecture 13 Video Compression Techniques 12 VOP-based Motion Compensation (MC) • MC-based VOP coding in MPEG-4 again involves three steps: (a) Motion Estimation. (b) MC-based Prediction. (c) Coding of the prediction error. • Only pixels within the VOP of the current (Target) VOP are considered for matching in MC. • To facilitate MC, each VOP is divided into many macroblocks (MBs). MBs are by default 16x16 in luminance images and 8x8 in chrominance images.ECE160 Spring 2011 Lecture 13 Video Compression Techniques 13 VOP-based Motion Compensation (MC) • MPEG-4 defines a rectangular bounding box for each VOP. – The macroblocks that are entirely within the VOP are referred to as Interior Macroblocks. – The macroblocks that straddle the boundary of the VOP are called Boundary Macroblocks. • To help matching every pixel in the target VOP and meet the mandatory requirement of rectangular blocks in transform codine (e.g., DCT), a pre-processing step of padding is applied to the Reference VOPs prior to motion estimation. Note: Padding only takes place in the Reference VOPs.ECE160 Spring 2011 Lecture 13 Video Compression Techniques 14 VOP-based Motion Compensation (MC) • Padding – For all Boundary MBs in the Reference VOP, Horizontal Repetitive Padding is invoked first, followed by Vertical Repetitive Padding. – Afterwards, for all Exterior Macroblocks that are outside of the VOP but adjacent to one or more Boundary MBs, Extended Padding is applied.ECE160 Spring 2011 Lecture 13 Video Compression Techniques 15 VOP-based Motion Compensation (MC) • An Example of Repetitive Padding (a) Original pixels within the VOP, (b) After Horizontal Repetitive Padding, (c) Followed by Vertical Repetitive Padding.ECE160 Spring 2011 Lecture 13 Video Compression Techniques 16 Motion Vector Coding • Let C(x+k, y+l) be pixels of the MB in Target VOP, and R(x+i+k, y+j+l) be pixels of the MB in Reference VOP. • A Sum of Absolute Difference (SAD) for measuring the difference between the two MBs can be defined as: N - the size of the MB. Map(p,q) = 1 when C(p,q) is a pixel within the target VOP, otherwise Map(p; q) = 0. • The vector (i,j) that yields the minimum SAD is adopted as the motion vector MV(u,v): (u,v) = [ (i; j) | SAD(i; j) is minimum, iε[−p,p], jε[−p,p] ] p is the maximal


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