An Introduction to Video Compression

Total Page:16

File Type:pdf, Size:1020Kb

An Introduction to Video Compression An Introduction to Video Compression Typical Camera An Introduction to Video Compression Image Image Video Sensor Processor Interface 4 AGENDA Image Sensors (CCD/CMOS) • Video Basics • Each cell is a monochrome – Analog Video detector – Digital Video • A filter array is used to make – Scanning Formats them sensitive to different color • Video Compression frequencies – Intra-Frame Coding • More green cells are used than red and blue cells because – Inter-Frame Coding human vision is more sensitive • Video Quality to green frequencies • Video Coding Standards • This is called a Bayer pattern • Audio Compression 2 5 Image Processing • Image processing internal to the camera converts the Bayer pattern to the desired Video Basics camera output format • Demosaicing and Interpolating algorithms are used to generate the output pixels • Typical outputs include RGB and YCrCb 3 6 Video Interface Analog Composite Video Formats • National Television Standard Committee (NTSC) – Interlaced: 2 fields/frame • Converts the camera’s pixel array data to an – 525 lines/frame, 262.5 lines/field output signal – 29.97 frames/second, 59.94 fields/second – 63.5 uSeconds/line • Horizontal/Vertical scanning of image array – Color burst: 3.58 MHz • Parallel to Serial conversion of pixel data • Phase Alternate Line (PAL) – Interlaced: 2 fields/frame • Synchronization, timing and status insertion – 625 lines/frame, 312.5 lines/field – 25 frames/second, 50 fields/second • Electrical signal generation – 64 uSeconds/line – Color burst: 4.43 MHz • Séquentiel couleur à mémoire (SECAM) 7 10 Analog Composite Video Waveform Digitized Composite Video Formats • NTSC – 720 horizontal x 480 vertical pixels – 2:1 Interlaced – 29.97 Frames per Second (59.94 Fields per Second) – 165.888 M Bits per Second • PAL – 720 horizontal x 576 vertical pixels – 2:1 Interlaced – 25 Frames per Second (50 Fields per Second) – 165.888 M Bits per Second 8 11 Analog Video Image Other Analog Formats • S-Video – Y – Luminance Signal – C – Chrominance Signal – Eliminates need for color separation filtering – Improved quality over Composite Video • YPrPb Component – Y – Luminance Signal – Pr – Red-Green Color Difference Signal – PB – Blue-Green Color Difference Signal – Supports High Definition Resolutions • RGB Component – Red, Green, and Blue Signals – Separate Sync signal – Sync on Green – Primarily a computer monitor format 9 12 Digital Broadcast Interfaces New Digital Broadcast Interfaces • Serial Digital Interface • New Serial Digital Interfaces – SMPTE 259 SDI (270Mbps) • 480i30 (720x480) – SMPTE 2081 6G-SDI (5.94Gbps) • 576i25 (720x576) • 4Kp30 (3840x2160) – SMPTE 292 HD-SDI (1.485Gbps, 1.485/1.001Gbps) – SMPTE 2082 12G-SDI (11.88Gbps) • 720p60 (1080x720) • 4Kp60 (3840x2160) • 1080i30 (1920x1080) • 1080p30 (1920x1080) – SMPTE 2083 24G-SDI (23.76Gbps) – SMPTE 424 3G-SDI (2.970Gbps, 2.970/1.001Gbps) • 8Kp30 (7680x4320) • 1080p60 (1920x1080) 13 16 Serial Digital Interface Line Broadcast Interface Machine Vision Interface • Fixed resolutions and • Random resolutions and frame rates frame rates • Unidirectional interface • Bidirectional interface • No control channel • Control channel • Fire and forget • Often requires handshake • Format indicated within • Format configured in the signal control channel • Coax cable • Most use complex cables • No trigger capability • Triggers • No camera power • Camera power 14 17 Serial Digital Interface Frame Machine Vision Interfaces • GigE Vision – Uncompressed video over UDP on 1-Gigabit and 10-Gigabit Ethernet networks – Cat5 cabling, Ethernet infrastructure – 125MB/s (1250MB/s) transfer rate • USB3 Vision – Same API as GigE Vision over USB 3.0 connections 15 18 Machine Vision Interfaces (Cont) Interlaced Scanning Format 1 • CoaXPress 264 2 – 6.25 Gbps over coax cable Retrace 265 – Group multiple cables (4 cables = 25 Gbps) 3 – Future expansion to 10 and 12.5 Gbps Odd field scan line • CameraLink – 26-pin Mini-D ribbon connector 524 – LVDS signal pairs, 2.04 Gbps 262 – Group multiple cables (2 cables = 4.08 Gbps) 525 – Video data, discrete signals, control channel 263 Even field scan line 19 22 Machine Vision Interfaces (Cont) Progressive Scanning Format 1 • IEEE-1394 FireWire 2 3 – Tree bus topology, bus master negotiations Retrace and self identification 4 5 – 400 and 800 Mbps (1600 and 3200 Mbps defined but not widely supported). Scan line – 4, 6 and 9 conductor connectors • DVI/HDMI 522 – 19 pin connector 523 524 – 48 Gbps data rate 525 – I2C Control channel – Copy Protection negotiation 20 23 Video Resolutions Interlace vs Progressive 21 24 Interlace vs Progressive Video Compression 25 28 Color Spaces The need for Video Compression • Digital Transmission. • Monochrome – Need to match video data rate to digital • Red, Green, Blue (RGB) communications system bandwidth. – Separate sync, Sync on Green • YIQ (NTSC, PAL) • Digital Storage. •YUV – Need to match video data rate to digital storage • YPbPr (Analog), YCbCr (Digital) system bandwidth. – Pb/Cb = Blue - Luma – Need to reduce storage capacity or increase storage – Pb/Cr = Red - Luma time. • HSV, HSB, HSL • Multiplexing •CMYK – Send more programs or other data over the same channel. 26 29 Other Characteristics Video Data Rates • Pixel Bit Depth • Uncompressed SD Video – 720x480, 30 fps, 16 bpp – 8, 10, 12, 14, 16 bits per component • 166 Mbps • Chroma Sampling • Uncompressed HD Video – 4:4:4, 4:2:2, 4:2:0, 4:0:0 – 1920x1080, 60 fps, 16 bpp • 1,990 Mbps • Uncompressed UHD Video – 7680x4320, 120 fps, 16 bpp • 63,701 Mbps 27 30 Digital Transmission Rates Types of Compression • Lossless • Transmission System Data Rates – Output image is numerically identical to the original image on a pixel-by-pixel basis. – Ethernet: 10/100 Mbps, 1/10 Gbps – Only statistical redundancy is reduced – OC12: 622 Mbps – Compression ratio is usually low – 2:1 to 4:1 – OC3: 155 Mbps – Reversible (infinite compress/decompress cycles) – DS3: 45 Mbps • Lossy – T1: 1.544 Mbps – Output image is numerically degraded relative to the original. – DSO: 64 Kbps – Statistical and perceptual redundancy is reduced – Modem: 33.6 Kbps – High compression due to reduction of perceptual – Cellular: 9600 redundancy – Can be visually lossless – Irreversible (compress/decompress degrades images) 31 34 Digital Storage Capacity Video Compression Standards • Uncompressed SD Video: 166 Mbps PRE-PROCESS POST- BIT- PROCESS -Noise Filter STREAM - Signal – 1 Min. Clip = 1.24 G Bytes -Scaling ENCODE DECODE Enhancement - Filter - Error – 30 Min. TV Show = 37.3 G Bytes Concealment – 2 Hour Movie = 149.3 G Bytes • Uncompressed HD Video: 1,990 Mbps • Functions Standardized • Functions Not Standardized – 1 Min. Clip = 14.9 G Bytes – Bit stream syntax – Pre-processing – 30 Min. TV Show = 447.8 G Bytes – How the decoder interprets the bit • Filtering, scaling, noise reduction stream – 2 Hour Movie = 1.79 T Bytes – Encoding strategy • Uncompressed UHD Video: 63,701 Mbps • Mode Selection • Quantizer Selection – 1 Min. Clip = 477.8 G Bytes • Block Pattern Selection – 30 Min. TV Show = 14.3 T Bytes • Motion Estimation – 2 Hour Movie = 57.3 T Bytes – Post-filter • Scaling, block filtering, error 32 35 concealment Digital Storage Devices Preprocessing (1/5) • Noise Reduction •CD – 185 to 870 M Bytes (various formats) – Filter out high frequency information and improves compression efficiency •DVD – 1.46 to 17.08 G Bytes (SS, SD, SL, DL) – Spatial Noise Reduction • BluRay Disk • Reduces high frequency information within a picture – 25 G Bytes (50 GB for dual layer disks) – Temporal Noise Reduction • Disk Drives • Reduces high frequency information between –> 1 T Byte frames 33 36 Preprocessing (2/5) Preprocessing (5/5) • Color representation • Resolution Reduction – Reduces the amount of spatial information – Reduces the amount of that needs to be compressed spatial information that needs to be 4:4:4 4:2:2 4:2:0 compressed – Scaling • Maintains field of view 24 16 12 Bits/Pixel Bits/Pixel Bits/Pixel 37 40 Y Cr Cb Preprocessing (3/5) Intra-Frame Coding • Resolution Reduction • Removes the redundancies within a frame – Reduces the amount of • Each frame is encoded separately without spatial information that regard to adjacent frames needs to be compressed • Similar to JPEG – Cropping • Maintains pixel resolution 38 41 Preprocessing (4/5) Encoding Stages • Frame Rate Reduction • Signal Analysis – Reduces the amount of temporal information that needs to be compressed – Transform from spatial domain to another domain that is easier to compress 12 3456 • Quantization Video Sequence – 30 Frames per Second – Discard less important information 135XXX • Variable Length Coding – Last stage of efficient coding Video Sequence – 15 Frames per Second 39 42 Video Compression System Transform Coding by Discrete Cosine Transform (DCT) Signal Analysis Variable length coding Segmentation of a frame INTRAFRAME Quantization (entropy coding) - Predictive into blocks of pixels + 1D, 2D predictor - Variable precision -Fixed + Fixed, adaptive + Huffman - Block transform + B + DCT - Visibility matrix + Comma + Karhunen Loeve Uncompressed - Prediction + 2 dimensional COMPRESSED + Hadamard input error (run length/COEFF) OUTPUT + Fourier e.g. 8 bits/pixel - Fixed, adaptive + Haar - Transform - Adaptive - Sub-band filtering coefficients + Conditional + Unconstrained 8x8 - Lossy, lossless + Arithmetic rectangular blocks - Filter energy + One, two passes Coefficients + QMF, other filters levels 8x8 Pixels + Wavelets - Scalar, vector - Lossless + Pyramidal - Block pattern matching (VQ) - Fractals
Recommended publications
  • On Computational Complexity of Motion Estimation Algorithms in MPEG-4 Encoder
    On Computational Complexity of Motion Estimation Algorithms in MPEG-4 Encoder Muhammad Shahid This thesis report is presented as a part of degree of Master of Science in Electrical Engineering Blekinge Institute of Technology, 2010 Supervisor: Tech Lic. Andreas Rossholm, ST-Ericsson Examiner: Dr. Benny Lovstrom, Blekinge Institute of Technology Abstract Video Encoding in mobile equipments is a computationally demanding fea- ture that requires a well designed and well developed algorithm. The op- timal solution requires a trade off in the encoding process, e.g. motion estimation with tradeoff between low complexity versus high perceptual quality and efficiency. The present thesis works on reducing the complexity of motion estimation algorithms used for MPEG-4 video encoding taking SLIMPEG motion estimation algorithm as reference. The inherent prop- erties of video like spatial and temporal correlation have been exploited to test new techniques of motion estimation. Four motion estimation algo- rithms have been proposed. The computational complexity and encoding quality have been evaluated. The resulting encoded video quality has been compared against the standard Full Search algorithm. At the same time, reduction in computational complexity of the improved algorithm is com- pared against SLIMPEG which is already about 99 % more efficient than Full Search in terms of computational complexity. The fourth proposed algorithm, Adaptive SAD Control, offers a mechanism of choosing trade off between computational complexity and encoding quality in a dynamic way. Acknowledgements It is a matter of great pleasure to express my deepest gratitude to my ad- visors Dr. Benny L¨ovstr¨om and Andreas Rossholm for all their guidance, support and encouragement throughout my thesis work.
    [Show full text]
  • Kulkarni Uta 2502M 11649.Pdf
    IMPLEMENTATION OF A FAST INTER-PREDICTION MODE DECISION IN H.264/AVC VIDEO ENCODER by AMRUTA KIRAN KULKARNI Presented to the Faculty of the Graduate School of The University of Texas at Arlington in Partial Fulfillment of the Requirements for the Degree of MASTER OF SCIENCE IN ELECTRICAL ENGINEERING THE UNIVERSITY OF TEXAS AT ARLINGTON May 2012 ACKNOWLEDGEMENTS First and foremost, I would like to take this opportunity to offer my gratitude to my supervisor, Dr. K.R. Rao, who invested his precious time in me and has been a constant support throughout my thesis with his patience and profound knowledge. His motivation and enthusiasm helped me in all the time of research and writing of this thesis. His advising and mentoring have helped me complete my thesis. Besides my advisor, I would like to thank the rest of my thesis committee. I am also very grateful to Dr. Dongil Han for his continuous technical advice and financial support. I would like to acknowledge my research group partner, Santosh Kumar Muniyappa, for all the valuable discussions that we had together. It helped me in building confidence and motivated towards completing the thesis. Also, I thank all other lab mates and friends who helped me get through two years of graduate school. Finally, my sincere gratitude and love go to my family. They have been my role model and have always showed me right way. Last but not the least; I would like to thank my husband Amey Mahajan for his emotional and moral support. April 20, 2012 ii ABSTRACT IMPLEMENTATION OF A FAST INTER-PREDICTION MODE DECISION IN H.264/AVC VIDEO ENCODER Amruta Kulkarni, M.S The University of Texas at Arlington, 2011 Supervising Professor: K.R.
    [Show full text]
  • A Survey Paper on Different Speech Compression Techniques
    Vol-2 Issue-5 2016 IJARIIE-ISSN (O)-2395-4396 A Survey Paper on Different Speech Compression Techniques Kanawade Pramila.R1, Prof. Gundal Shital.S2 1 M.E. Electronics, Department of Electronics Engineering, Amrutvahini College of Engineering, Sangamner, Maharashtra, India. 2 HOD in Electronics Department, Department of Electronics Engineering , Amrutvahini College of Engineering, Sangamner, Maharashtra, India. ABSTRACT This paper describes the different types of speech compression techniques. Speech compression can be divided into two main types such as lossless and lossy compression. This survey paper has been written with the help of different types of Waveform-based speech compression, Parametric-based speech compression, Hybrid based speech compression etc. Compression is nothing but reducing size of data with considering memory size. Speech compression means voiced signal compress for different application such as high quality database of speech signals, multimedia applications, music database and internet applications. Today speech compression is very useful in our life. The main purpose or aim of speech compression is to compress any type of audio that is transfer over the communication channel, because of the limited channel bandwidth and data storage capacity and low bit rate. The use of lossless and lossy techniques for speech compression means that reduced the numbers of bits in the original information. By the use of lossless data compression there is no loss in the original information but while using lossy data compression technique some numbers of bits are loss. Keyword: - Bit rate, Compression, Waveform-based speech compression, Parametric-based speech compression, Hybrid based speech compression. 1. INTRODUCTION -1 Speech compression is use in the encoding system.
    [Show full text]
  • 1. in the New Document Dialog Box, on the General Tab, for Type, Choose Flash Document, Then Click______
    1. In the New Document dialog box, on the General tab, for type, choose Flash Document, then click____________. 1. Tab 2. Ok 3. Delete 4. Save 2. Specify the export ________ for classes in the movie. 1. Frame 2. Class 3. Loading 4. Main 3. To help manage the files in a large application, flash MX professional 2004 supports the concept of _________. 1. Files 2. Projects 3. Flash 4. Player 4. In the AppName directory, create a subdirectory named_______. 1. Source 2. Flash documents 3. Source code 4. Classes 5. In Flash, most applications are _________ and include __________ user interfaces. 1. Visual, Graphical 2. Visual, Flash 3. Graphical, Flash 4. Visual, AppName 6. Test locally by opening ________ in your web browser. 1. AppName.fla 2. AppName.html 3. AppName.swf 4. AppName 7. The AppName directory will contain everything in our project, including _________ and _____________ . 1. Source code, Final input 2. Input, Output 3. Source code, Final output 4. Source code, everything 8. In the AppName directory, create a subdirectory named_______. 1. Compiled application 2. Deploy 3. Final output 4. Source code 9. Every Flash application must include at least one ______________. 1. Flash document 2. AppName 3. Deploy 4. Source 10. In the AppName/Source directory, create a subdirectory named __________. 1. Source 2. Com 3. Some domain 4. AppName 11. In the AppName/Source/Com directory, create a sub directory named ______ 1. Some domain 2. Com 3. AppName 4. Source 12. A project is group of related _________ that can be managed via the project panel in the flash.
    [Show full text]
  • Video Basics ---Major Ref
    Video Basics ---major ref. From Ch.5 of textbook 2 ■ Introduction ---- video industry ■ Video Imaging ---- video scan, aspect ratio ■ Color and Composite & component systems ■ From Analog To Digital Video ■ Spatial Conversions ---- video formats ■ Temporal Conversions ■ Mixing And Keying @NTUEE 1 DSP/IC Lab Video Environments Satellite DVB-S downstream(max 90 Mbps) DSS Cable Modem Cable Network DVB-C downstream(max 40 Mbps) OpenCable Home Connection DSTB IEEE 1394 / USB Ethernet 10 Mbps….. Terrestrial DVB-T/ ATSC (Plug&Play , high-data-rate) Interaction Channel DTV set DirecPC/ DirecDuo (1-way / 2-way)1. Satellite( fast PSTN/ ISDN 2. Cable Modem ( QPSK, TCP / IP for PSTN/ ISDN modem 3. SDSL / ADSL / VDSL ….. @NTUEE 2 DSP/IC Lab 1 Video Service Environments Service Provision HFC POTS Wireless Cable DVB-S DVB-C (Full Service (xDSL access) (MMDS) DVB-T (high speed BB) (Cable Modem) Network) TCP / IP Hybrid Services DSTB Residential LAN (IR, RF, Wired) @NTUEE 3 DSP/IC Lab F ãñìµ@ûì > r Gï=.1 *<ÎPU½ÿ½CD *¶1nñG *ÐÍV PC ;^éuu *ñ<uïÚí Internet w7Home SpoppingHome Banking…. *PPV 2âSaDO"H2<_G.(VOD)ÛÚí ö^éGï=. *ö7GïA2Uf÷ ß[1nЯrn1<t *>1ʺ=.²ÁÞ+Gï STBw¯Gï=.1Æ *"Gï=.²2òGï STB Þ1äh¼oZÐõ1"2¤ Gï STB aöÞ^éGï=.> * õ1n<tñ)ËàÁréï=éC 4 *Gï>h Úü¶Êº=.AÓ-I FMMedium Wave ¤µÚí1 / R *Gï>Áä÷1 transm ittersÇt1ä÷ *Gï>r1ñ² ô<Gï=.> *Î BBC aGï=.Ú7ÂbÍÈzéúrp¾câ> DTT > *BDB 2£< 30! DTT nÚí *­~£U>;HÞr> HDTV/SDTV > *BSkyB ~£ 6 ´[uSr> 200 !nGïá#Úí *TCIComcastÛUÀ MSOb 1997 £¦¬[àGï Cable Úí *Flextech $} BBC >Ë1Gïn(å UKFM) ö´^éGï=.> *1994 £¦­Gï DBS I 1996 £¦[JGïá#r> *1997£¦Gï Cable Úír> *1998 £­Î DTT r>ʺ=.²ñhk¶ 12ß 15£1´t Ngñ·ëæJUJT702::9 @NTUEE 4 DSP/IC Lab 2 Applications of Digital Video ¸®ñ *Î]]XÇæ *Internetÿñ *ñ'$7Åg e-mailì½WWW..
    [Show full text]
  • Video Coding Standards
    Video coding standards Video signals represent sequences of images or frames which can be transmitted with a rate from 15 to 60 frames per second (fps), that provides the illusion of motion in the displayed signal. Unlike images they contain the so-called temporal redundancy. Temporal redundancy arises from repeated objects in consecutive frames of the video sequence. Such objects can remain, they can move horizontally, vertically, or any combination of directions (translation movement), they can fade in and out, and they can disappear from the image as they move out of view. Temporal redundancy Motion compensation A motion compensation technique is used to compensate the temporal redundancy of video sequence. The main idea of the this method is to predict the displacement of group of pixels (usually block of pixels) from their position in the previous frame. Information about this displacement is represented by motion vectors which are transmitted together with the DCT coded difference between the predicted and the original images. Motion compensation Image VLC DCT Quantizer Buffer - Dequantizer Coded DCT coefficients. IDCT Motion compensated predictor Motion Motion vectors estimation Decoded VL image Buffer Dequantizer IDCT decoder Motion compensated predictor Motion vectors Motion compensation Previous frame Current frame Set of macroblocks of the previous frame used to predict the selected macroblock of the current frame Motion compensation Previous frame Current frame Macroblocks of previous frame used to predict current frame Motion compensation Each 16x16 pixel macroblock in the current frame is compared with a set of macroblocks in the previous frame to determine the one that best predicts the current macroblock.
    [Show full text]
  • Arxiv:2004.10531V1 [Cs.OH] 8 Apr 2020
    ROOT I/O compression improvements for HEP analysis Oksana Shadura1;∗ Brian Paul Bockelman2;∗∗ Philippe Canal3;∗∗∗ Danilo Piparo4;∗∗∗∗ and Zhe Zhang1;y 1University of Nebraska-Lincoln, 1400 R St, Lincoln, NE 68588, United States 2Morgridge Institute for Research, 330 N Orchard St, Madison, WI 53715, United States 3Fermilab, Kirk Road and Pine St, Batavia, IL 60510, United States 4CERN, Meyrin 1211, Geneve, Switzerland Abstract. We overview recent changes in the ROOT I/O system, increasing per- formance and enhancing it and improving its interaction with other data analy- sis ecosystems. Both the newly introduced compression algorithms, the much faster bulk I/O data path, and a few additional techniques have the potential to significantly to improve experiment’s software performance. The need for efficient lossless data compression has grown significantly as the amount of HEP data collected, transmitted, and stored has dramatically in- creased during the LHC era. While compression reduces storage space and, potentially, I/O bandwidth usage, it should not be applied blindly: there are sig- nificant trade-offs between the increased CPU cost for reading and writing files and the reduce storage space. 1 Introduction In the past years LHC experiments are commissioned and now manages about an exabyte of storage for analysis purposes, approximately half of which is used for archival purposes, and half is used for traditional disk storage. Meanwhile for HL-LHC storage requirements per year are expected to be increased by factor 10 [1]. arXiv:2004.10531v1 [cs.OH] 8 Apr 2020 Looking at these predictions, we would like to state that storage will remain one of the major cost drivers and at the same time the bottlenecks for HEP computing.
    [Show full text]
  • Audio Coding for Digital Broadcasting
    Recommendation ITU-R BS.1196-7 (01/2019) Audio coding for digital broadcasting BS Series Broadcasting service (sound) ii Rec. ITU-R BS.1196-7 Foreword The role of the Radiocommunication Sector is to ensure the rational, equitable, efficient and economical use of the radio- frequency spectrum by all radiocommunication services, including satellite services, and carry out studies without limit of frequency range on the basis of which Recommendations are adopted. The regulatory and policy functions of the Radiocommunication Sector are performed by World and Regional Radiocommunication Conferences and Radiocommunication Assemblies supported by Study Groups. Policy on Intellectual Property Right (IPR) ITU-R policy on IPR is described in the Common Patent Policy for ITU-T/ITU-R/ISO/IEC referenced in Resolution ITU-R 1. Forms to be used for the submission of patent statements and licensing declarations by patent holders are available from http://www.itu.int/ITU-R/go/patents/en where the Guidelines for Implementation of the Common Patent Policy for ITU-T/ITU-R/ISO/IEC and the ITU-R patent information database can also be found. Series of ITU-R Recommendations (Also available online at http://www.itu.int/publ/R-REC/en) Series Title BO Satellite delivery BR Recording for production, archival and play-out; film for television BS Broadcasting service (sound) BT Broadcasting service (television) F Fixed service M Mobile, radiodetermination, amateur and related satellite services P Radiowave propagation RA Radio astronomy RS Remote sensing systems S Fixed-satellite service SA Space applications and meteorology SF Frequency sharing and coordination between fixed-satellite and fixed service systems SM Spectrum management SNG Satellite news gathering TF Time signals and frequency standards emissions V Vocabulary and related subjects Note: This ITU-R Recommendation was approved in English under the procedure detailed in Resolution ITU-R 1.
    [Show full text]
  • Discrete Cosine Transform for 8X8 Blocks with CUDA
    Discrete Cosine Transform for 8x8 Blocks with CUDA Anton Obukhov [email protected] Alexander Kharlamov [email protected] October 2008 Document Change History Version Date Responsible Reason for Change 0.8 24.03.2008 Alexander Kharlamov Initial release 0.9 25.03.2008 Anton Obukhov Added algorithm-specific parts, fixed some issues 1.0 17.10.2008 Anton Obukhov Revised document structure October 2008 2 Abstract In this whitepaper the Discrete Cosine Transform (DCT) is discussed. The two-dimensional variation of the transform that operates on 8x8 blocks (DCT8x8) is widely used in image and video coding because it exhibits high signal decorrelation rates and can be easily implemented on the majority of contemporary computing architectures. The key feature of the DCT8x8 is that any pair of 8x8 blocks can be processed independently. This makes possible fully parallel implementation of DCT8x8 by definition. Most of CPU-based implementations of DCT8x8 are firmly adjusted for operating using fixed point arithmetic but still appear to be rather costly as soon as blocks are processed in the sequential order by the single ALU. Performing DCT8x8 computation on GPU using NVIDIA CUDA technology gives significant performance boost even compared to a modern CPU. The proposed approach is accompanied with the sample code “DCT8x8” in the NVIDIA CUDA SDK. October 2008 3 1. Introduction The Discrete Cosine Transform (DCT) is a Fourier-like transform, which was first proposed by Ahmed et al . (1974). While the Fourier Transform represents a signal as the mixture of sines and cosines, the Cosine Transform performs only the cosine-series expansion.
    [Show full text]
  • Instant Savings!*
    Incredibly Easy! ® Was $64995** 18-55 NOW! VR Kit Mother’s Day D3100 ** Kit Includes 18-55mm VR Zoom-NIKKOR® Lens $ 95 549 * AFTER 14.2 UP TO 3 3" GUIDE MODE MEGAPIXELS FRAMES PER SECOND LCD MONITOR EASE OF USE $100 * Nikon Instant Savings 1080p INSTANT SAVINGS! HDVIDEO WITH FULL-TIME AUTOFOCUS White EXTRA INSTANT SAVINGS! Was $89990** Was $64995** Was $24995** NOW! NOW! NOW! ** $ 95** $ 95** $ 90 549 149 699 White Gift Pack Includes AFTER AFTER $100 $100 AFTER 1 NIKKOR VR 10mm-30mm * * Instant Savings + Instant Savings = $ Plum Zoom Lens, Red Leather 200 D3100 KIT INCLUDES 18-55MM DX VR BUY AN ADDITIONAL TELEPHOTO 55-200MM DX VR Camera Case & 8GB Memory Card Instant Savings* ZOOM-NIKKOR LENS. ZOOM-NIKKOR LENS AND SAVE $100 INSTANTLY. Gift Pack Includes Camera Case & 4GB Memory Card J1 White Gift Pack 3UNSET$RIVEs7ATERBURY#ENTER 64 Was $74995** AFTER ,OCATED/FF2OUTE !CROSSFROMTHE#OLD(OLLOW#IDER-ILL NOW! $ %VERYDAY,OW0RICES)N 3TORE3PECIALS New! 200 (AVEUSEDEQUIPMENT0UTITTOGOODUSE ** Instant 802-244-0883 $ 95 Savings* 3ELLORTRADE INYOUREQUIPMENTTODAY Gift Pack www.gmcamera.com 549 16 6x WIDE 3" HI-RES TOUCH Nikon MEGAPIXELS OPTICAL ZOOM LCD DISPLAY HD VIDEO $ 95** J1200182 KIT J1200182 KIT Was 219 AFTER * For details regarding Nikon’s Instant Savings Offers described in this fl yer, please visit: nikonusa.com/mothersdaykitoffers. Instant Savings offers $ on the COOLPIX S4300 Gift Pack, Nikon 1 J1 White Gift Pack, COOLPIX L26, COOLPIX L810, COOLPIX P310, COOLPIX S6300 and COOLPIX S9300 NOW! 90 are effective from 5/6/12 (or earlier) through 5/12/12. Instant Savings offers on the COOLPIX S30 and COOLPIX S3300 are effective from 5/6/12 ** through 5/19/12.
    [Show full text]
  • Canon XA25.Pdf
    XA25 Professional Camcorder The XA25 is a compact, high-performance professional camcorder designed specifically for “run-and-gun,” ENG-style shoots with enhanced I/O connectivity. The XA25 offers a unique combination of high-precision optics, outstanding image processing, multiple recording formats, flexible connectivity and intuitive user features. But its compact design does not mean compromised functionality – this small and lightweight camcorder meets the quality and performance standards necessary for use in a wide range of applications, including news gathering, law enforcement and military, education and documentary, among others. A powerful, all-new Genuine Canon 20x HD Video Lens with SuperRange Optical Image Stabilization and a new 8-Blade Circular Aperture extends user creativity; while a new 2.91 Megapixel Full HD CMOS Sensor and new DIGIC DV 4 Image Processor capture superb images with outstanding clarity. The camcorder features both MP4 (up to 35 Mbps) and AVCHD (up to 28 Mbps) codecs at up to 1080/50p resolution for virtually blur-free, high-quality capture of fast-moving subjects. Dual-band, built-in Wi-Fi® technology allows easy FTP file transfer and upload to the internet. A 3.5-inch OLED Touch Panel Display with the equivalent of 1.23 million dots of resolution offers a high contrast ratio, a wide- view angle and high-speed response, while a pair of SDHC/SDXC-compatible card slots enable Relay Recording, double-slot recording, and all-new Dual Recording, which enables the XA25 to capture video in different recording formats simultaneously. An HD/SD-SDI port allows uncompressed video with embedded audio and timecode data to be output to video editors, recorders, news trucks, workstations and other digital cinema/TV hardware.
    [Show full text]
  • Preview - Click Here to Buy the Full Publication
    This is a preview - click here to buy the full publication IEC 62481-2 ® Edition 2.0 2013-09 INTERNATIONAL STANDARD colour inside Digital living network alliance (DLNA) home networked device interoperability guidelines – Part 2: DLNA media formats INTERNATIONAL ELECTROTECHNICAL COMMISSION PRICE CODE XH ICS 35.100.05; 35.110; 33.160 ISBN 978-2-8322-0937-0 Warning! Make sure that you obtained this publication from an authorized distributor. ® Registered trademark of the International Electrotechnical Commission This is a preview - click here to buy the full publication – 2 – 62481-2 © IEC:2013(E) CONTENTS FOREWORD ......................................................................................................................... 20 INTRODUCTION ................................................................................................................... 22 1 Scope ............................................................................................................................. 23 2 Normative references ..................................................................................................... 23 3 Terms, definitions and abbreviated terms ....................................................................... 30 3.1 Terms and definitions ............................................................................................ 30 3.2 Abbreviated terms ................................................................................................. 34 3.4 Conventions .........................................................................................................
    [Show full text]