CS代考 VIDEO COMPRESSION – cscodehelp代写

VIDEO COMPRESSION
VIDEO COMPRESSION
Dr. – CS576 Lecture 6 Page 1

TOPICS TO BE COVERED
TOPICS TO BE COVERED
Introduction
• Video Characteristics and Types • Applications
Why is Video Compression different from Image Compression?
Modalities of Video Coding – Intraframe and Interframe
Motion Vectors and Motion Compensation Techniques
Standards and Implementation • H.261 (ITU)
• H.263 (ITU)
• MPEG-1 (ISO)
• MPEG-2 (ISO)
• H.264 / MPEG-4 AVC • HEVC
Dr. – CS576 Lecture 6 Page 2

INTRODUCTION
INTRODUCTION
Digital Video in comparison to Analog Video
Advantages of Digital Video
• Higher levels of quality
• Easily manipulated
• Easily stored and copied or duplicated
• Easily transmitted over networks
• Easy integration with other digital media
Digital Video is characterized by
• Frame rate (creates illusion of motion) • Frame dimension (width and height)
• Pixel Depth (bits per pixel)
Dr. – CS576 Lecture 6 Page 3

APPLICATIONS OF DIGITAL VIDEO
APPLICATIONS OF DIGITAL VIDEO
Application
Frame Rate
Dimensions
Pixel Depth
Multimedia
15
320×240
16
Entertainment (TV)
25
640×480
16
Industry Applications
5
640×480
8-12
Video Telephony
10
320×240
8-12
HDTV
25
1920×1080
24
Dr. – CS576 Lecture 6 Page 4

WHY IS VIDEO COMPRESSION DIFFERENT
WHY IS VIDEO COMPRESSION DIFFERENT FROM IMAGE COMPRESSION?
Video consists of a stream of images – but is also characterized by –
• Scanning format (progressive, interlaced) • Frame size (typically standardized)
• Frame rate (15-30 Hz)
Like images Spatial Redundancy exists in each frame
Temporal Redundancy in between frames and can be exploited for compression reasons!
• Areas of the image in the sequence may remain constant, or
• Areas tend to move in a predictable fashion, and therefore can be “predicted” from frame to frame
Dr. – CS576 Lecture 6 Page 5

EXPLOITING TEMPORAL REDUNDANCY
EXPLOITING TEMPORAL REDUNDANCY
Frame n Frame n+1 Frame (n+1) – Frame n
Frame n Frame n+1 Frame (n+1) – Frame n
Successive frames in a video. (low motion on top, high motion at the bottom). Also shown is the frame difference of the Y channel. The difference large in high motion compared to low motion.
Dr. – CS576 Lecture 6 Page 6

EXPLOITING TEMPORAL REDUNDANCY –
EXPLOITING TEMPORAL REDUNDANCY – MOTION COMPENSATION
This prediction is called Motion Compensation and is of two types –
• Local Motion Compensation (or just motion compensation)
• Global Motion Compensation
Each video frame may be encoded differently depending on whether to use spatial or temporal redundancies
Dr. – CS576 Lecture 6 Page 7

MODALITIES OF VIDEO COMPRESSION
MODALITIES OF VIDEO COMPRESSION
Depending on which mode (spatial or temporal) you want to exploit for compression reasons, you have two modes of compression for video
Intraframe
• Each frame is encoded as an individual entity
(like an “image”)
• Uses Image Compression techniques (eg DCT)
Interframe
• Predictive Encoding but for the temporal domain
• Instead of encoding the current frame directly,
we encode the difference between the current
frame and a prediction based on previous frames
• Term Used – Motion Compensation
Dr. – CS576 Lecture 6 Page 8

INTRAFRAME CODING
INTRAFRAME CODING
These frames are compressed using a combination of a Lossy Scheme such as Transform Coding or Subsampling/Quantization and Lossless Entropy Coding such Huffman or Arithmetic.
For example, the MPEG/ITU Standard compresses these frames as discussed in the previous lecture –
• Get 8×8 blocks (for each component)
• DCT on each block
• Quantization of all coefficients
• AC zigzag ordering
• DC  DPCM  (size) (value)
• AC  Runlength Encoded  (runlength, size) (value)
• Both AC and DC Coefficients get Huffman
encoded to form a bit stream
Dr. – CS576 Lecture 6 Page 9

CHANGES FROM FRAME TO FRAME
CHANGES FROM FRAME TO FRAME
What can happen to a pixel (or pixel region) from one frame to another?
• Nothing! – Like an unchanging background – so do we need to encode information here?
• Changes (slight) due to quantization and noise
• Changes due to the motion of the object
• Changes due to motion of the camera
• Changes due to environment and lighting
If nothing has changed – no need to encode
If changes in pixel color or pixel value due to motion of object or camera, maybe we can predict how the pixels have moved, thereby needing to encode only the change vector
Dr. – CS576 Lecture 6 Page 10

MOTION VECTOR
MOTION VECTOR
Lets assume that if a pixel has moved from frame to frame, the color of the pixel has not changed
In other words: A point (x,y) in frame n+1 with color cn+1(x,y) corresponds to some point (x’,y’) in frame n.
cn+1(x , y) = cn(x’ , y’)
If we call this displacement or motion vector d = (dx, dy)
then we have
d = (dx, dy) = (x, y) – (x’, y’)
Dr. – CS576 Lecture 6 Page 11

MOTION VETOR EXAMPLE
MOTION VETOR EXAMPLE
Dr. – CS576 Lecture 6 Page 12

MOTION COMPENSATION
MOTION COMPENSATION
If our motion assumption is (approximately) valid, then cn+1(x,y) can be predicted from cn (x-dx ,y-dy )
Like with differential encoding, we encode and transmit the residual error
e(x,y)=cn+1(x,y)- cn(x-dx,y-dy)
We must also encode and transmit the motion vectors
(dx , dy)
If we use lossy encoding, we should use a closed-loop scheme!
Dr. – CS576 Lecture 6 Page 13

MOTION COMPENSATION – MACROBLOCKS
MOTION COMPENSATION – MACROBLOCKS
Do we need to compute and transmit one motion vector d per pixel?
• Computationally intensive! • Lots of data to send
Instead: transmit only 1 motion vector per groups of pixels called macroblock (e.g., 16×16 pixels)
Advantage & Disadvantages:
Fewer motion vectors to be transmitted
Faster computationally
Less precise motion prediction if motion is not constant within the macroblock (e.g., if macroblock covers the edge of a moving object)
Dr. – CS576 Lecture 6 Page 14

MACROBLOCK MOTION VECTORS – EXAMPLE
MACROBLOCK MOTION VECTORS – EXAMPLE
Frame at time n
Dr. – CS576 Lecture 6 Page 15

MACROBLOCK MOTION VECTORS – EXAMPLE
MACROBLOCK MOTION VECTORS – EXAMPLE
Frame at time n-1 showing motion vectors computed using frame at time n
Dr. – CS576 Lecture 6 Page 16

MACROBLOCK MOTION VECTORS – EXAMPLE
MACROBLOCK MOTION VECTORS – EXAMPLE
Difference between frames n and n-1, without motion compensation
Dr. – CS576 Lecture 6 Page 17

MACROBLOCK MOTION VECTORS – EXAMPLE
MACROBLOCK MOTION VECTORS – EXAMPLE
Difference between frames n and n-1, with motion compensation
Dr. – CS576 Lecture 6 Page 18

CLOSED LOOP MOTION COMPENSATION
CLOSED LOOP MOTION COMPENSATION
Decoder
Dr. – CS576 Lecture 6 Page 19

A NOTE ON FRAME SEGMENTATION
A NOTE ON FRAME SEGMENTATION
This also refers to deciding a size and shape of these macroblocks that are used in computing motion
Normally a frame is divided in non-overlapping blocks of a certain size B (16×16) and shape (square). Block size and shape affects the performance of compression
Issues
• Large B  fewer blocks to search  fewer
motion vectors to encode
• For large B, the movement of objects do not
coincide with boundaries of B  larger errors or residuals that need to be encoded
Thus block size represents a trade off between minimizing the number of motion vectors and maximizing the quality of the matching blocks
Dr. – CS576 Lecture 6 Page 20

MACROBLOCKS AT MOTION BOUNDARIES
MACROBLOCKS AT MOTION BOUNDARIES
Dr. – CS576 Lecture 6 Page 21

SEARCHING AND BLOCK MATCHING
SEARCHING AND BLOCK MATCHING
If the difference between the target block and the candidate block at the same position in the past frame is below some threshold  no motion, else search
Block matching is the most time consuming – for accurate results you need to do an exhaustive search which is – given a block B in the current frame search for a match block A in the entire previous frame. This may be further optimized: Instead of entire frame,
• Limit search to a region • Logarithmic Search
• Hierarchical
In practice, this search can be limited to a range around the “target block”
Dr. – CS576 Lecture 6 Page 22

MATCHING CRITERIA
MATCHING CRITERIA
Various Criteria are used to decided whether the current block matches a target block –
• Mean Absolute Difference (MAD)
• Mean Square Difference (MSD)
• Pel Difference Classification (PDC) • Integral Projection
(Formulae of each to be mentioned in the lecture …)
Dr. – CS576 Lecture 6 Page 23

MOTION COMPENSATION – ALGORITHM
MOTION COMPENSATION – ALGORITHM
Given a sequence of frames (each have macroblocks) – Encode first frame as IntraFrame
For each corresponding macroblock of next frame and current frame, find the difference.
• If difference less than threshold  no motion, find residual error
• If difference above threshold  may be motion, look in search range to find a matching block using matching criteria discussed above. Note motion vector and residual error
If difference (or total residual error) is too large for a majority of macroblocks, and/or after regular intervals encode the current frame as an Intraframe and proceed to previous step
Dr. – CS576 Lecture 6 Page 24

MOTION COMPENSATION – ENCODING
MOTION COMPENSATION – ENCODING
There are two things to encode here:
• Motion Vector for every macroblock
• Difference or residual for every macroblock
Motion vectors are typically encoded losslessly (similar to JPEG lossless mode)
The residuals e(x, y) are encoded lossy + lossless (DCT + Entropy) producing variable bit rate (VBR).
If smooth motion or no motion:
• Motion prediction is good (residuals are small) • Entropy coded with few bits
If complex motion or change of scene:
• Motion prediction is bad (residual are large) • Entropy coded with many bits
Dr. – CS576 Lecture 6 Page 25

MAIN PROPOSED DIGITAL VIDEO STANDARDS
MAIN PROPOSED DIGITAL VIDEO STANDARDS
ITU standards
• H.261 (videoconferences over ISDN)
• H.263 (videoconferencing and video telephony
over POTS)
• H.264
ISO standards
• MPEG-1 (movies on CD-ROM)
• MPEG-2 (digital television, movies on DVD) • MPEG-4 (more versatile distribution)
• MPEG4 AVC (Advanced Video Coding)
• HEVC
VCEG
Dr. – CS576 Lecture 6 Page 26

ITU H.261
ITU H.261
The ITU H.261 standard was initially designed for ISDN and was intended to support video conferencing applications, which have relatively small amounts of motion (mainly head and shoulder movements).
It and supports the following features
• Produces bit-rates of k x 64 Kb/s
• Only non-interlaced video
• Only CIF and QCIF formats
• Can encode in intraframe and interframe mode
Intraframe: DCT on 8×8 blocks (like JPEG)
Interframe: computes motion vectors on 16×16 macroblocks from a reference frame, which may be a frame encoded in intraframe or interframe mode.
Dr. – CS576 Lecture 6 Page 27

ITU H.263
ITU H.263
Supports a wider range of picture formats, including 4CIF (704×576) and 16CIF (1408×1152).
H.263 is part of the H.324 standard for communication over POTS with a modem with a maximum available rate of 33.6 Kb/s and a normal available bit-rate of 26-28 Kb/s
The other components of H.324 are: G.723 speech codec standard, framing and control protocols (H.223 and H.245) and data-sharing protocols
Based on the same DCT and motion compensation technique used in H.261. Incremental improvements are
• Half-pixel motion compensation
• Advanced motion prediction mode, including • Overlapped block motion estimation
• Bi-directional motion estimation
Dr. – CS576 Lecture 6 Page 28

BIDIRECTIONAL MOTION COMPENSATION
BIDIRECTIONAL MOTION COMPENSATION
A block of a bidirectionally coded frame is predicted from both a previous frame and a later frame
Bidirectional Motion Compensation implies:
• A delay (to decode the current frame, we need to
have received and decoded a later frame)
• Different order between the sequence of acquired
and displayed frames and the sequence of encoded frames
Dr. – CS576 Lecture 6 Page 29

BIDIRECTIONAL MOTION EXAMPLE
BIDIRECTIONAL MOTION EXAMPLE
Dr. – CS576 Lecture 6 Page 30

MPEG-1 VIDEO
MPEG-1 VIDEO
MPEG-1: true multimedia standard with specifications for coding and transmission of audio, video and data streams in a series of synchronized, mixed packets
Driving focus: storage of multimedia content on CD- ROMs (1.4 Mb/s, 600 MB)
Picture format: SIF
• non-interlaced: 352×288, 25 f/s
• interlaced: 354×240, 30 non-interlaced f/s
Quality: VHS VCR-like video and audio
Dr. – CS576 Lecture 6 Page 31

MPEG-1 VIDEO (2)
MPEG-1 VIDEO (2)
Coding mechanism similar to H.26x
Three types of frames:
• I-frames (coded in intraframe mode)
• P-frames (coded with motion compensation
using as reference a previous I or P frame) • B-frames (coded with bidirectional motion
compensation based on a previous and later I or P frame)
Dr. – CS576 Lecture 6 Page 32

ACQUISITION/TRANSMISSION ORDER
ACQUISITION/TRANSMISSION ORDER
Dr. – CS576 Lecture 6 Page 33

MPEG-2
MPEG-2
MPEG-2 was designed to provide the capability for compressing, coding, and transmitting high-quality, multichannel, multimedia signals over broadband networks
MPEG-2 standard specifies the requirements for video coding, audio coding, systems coding for combining coded audio and video with user defined private data streams, as well as conformance testing
MPEG-2 video was originally designed for high-quality encoding of interlaced video from standard TV (4-9 Mb/s). Over time, the MPEG-2 video standard was expanded to include high-resolution video (such as HDTV), as well as hierarchical (or scalable or layered) video coding
Dr. – CS576 Lecture 6 Page 34

MPEG-2 SYSTEMS LEVEL
MPEG-2 SYSTEMS LEVEL
Because MPEG-2 was designed as a transmission standard, it supports a variety of packet formats and provides error-correction capability for noisy channels
Two kinds of streams:
• Program stream: uses long and variable-length
packets. Well suited for software-based
processing and error-free environments
• Transport stream: uses fixed-length packets (188
bytes). Well-suited for delivering compressed video and audio over error-prone channels such as CATV networks and satellite transponders. Allows one to include multiple programs in a single stream
Dr. – CS576 Lecture 6 Page 35

NON-SCALABLE MPEG-2 VIDEO ENCODER
NON-SCALABLE MPEG-2 VIDEO ENCODER
Dr. – CS576 Lecture 6 Page 36

SCALABLE MPEG-2 VIDEO
SCALABLE MPEG-2 VIDEO
The coded representation (bit-stream) is generated in such a way that decoders of various complexities are able to decode video of different resolution/quality from the same bit stream
If the bitstream is truly scalable, decoders of different complexities can coexist: inexpensive decoders would be expected to decode only small portions of the same bitstream producing basic quality pictures, while more sophisticated and expensive decoders will produce higher quality pictures
Finds applications in networks with multi-quality video services and windowed video on computer workstations
Dr. – CS576 Lecture 6 Page 37

SCALABILITY LAYERS IN MPEG-2 VIDEO
SCALABILITY LAYERS IN MPEG-2 VIDEO
Input video goes through a pre-processor producing a base layer signal and an enhancement layer
• Base layer is decoded independently by a standard MPEG-2 non-scalable video encoder
• Enhancement layer is encoded with respect to the base layer by a MPEG-2 enhancement encoder
Dr. – CS576 Lecture 6 Page 38

SCALABLE MPEG-2 VIDEO ENCODER
SCALABLE MPEG-2 VIDEO ENCODER
Dr. – CS576 Lecture 6 Page 39

H.264 OR MPEG-4 AVC
H.264 OR MPEG-4 AVC
Latest Video Coding standard issued by ITU-VCEG and ISO-MPEG
Better video quality than earlier codec standards at same or less bitrates.
Designed for technical solutions addressing
• Broadcast over cable, satellite, Cable Modem. DSL
• High quality interactive storage on
optical/magnetic devices – DVD
• Video on Demand over DSL, Cable Modem,
wireless
• MMS over Ethernet, LAN, Wireless
Industry excitement over applications and deployments using H.264 / AVC
Dr. – CS576 Lecture 6 Page 40

FEATURES OF H.264 / AVC
FEATURES OF H.264 / AVC
Features that make this codec better
• Directional spatial prediction for Intra Coding
• Small block size transform
• Variable block size motion compensation
• QPEL – quarter pixel accurate prediction
• Multiple reference picture motion compensation
for P frames
• Bi prediction for B frames (not necessarily one
future and one past)
Dr. – CS576 Lecture 6 Page 41

Dr. – CS576 Lecture 6 Page 42

• Macroblocks Vs CTUs (Coding Tree Units) • Broadcast TV industry, MSFT, AAPL
• Google and VP9
• Alliance for OpenMedia and AV1 format
Dr. – CS576 Lecture 6 Page 43