Cloud Encoding Service

Total Page:16

File Type:pdf, Size:1020Kb

Cloud Encoding Service Cloud Encoding Service Scalability, speed & control San Francisco Chicago Seattle New York Amsterdam Austria Hong Kong Sao Paulo bitmovin.com Advantages of a flexible encoding stack Reduce Video Streaming Costs Simplify Workflows, Integration and Support Encode with state of the art codecs, like HEVC, VP9 and AV1, We know how painful it can be to integrate an inflexible to reduce file sizes by up to 50% compared to optimized H.264. encoding API or fiddle around with ffmpeg on the command Multi-codec streaming allows you to stream at halve the cost line. The Bitmovin API was designed to make your integrations while maintaining the same perceptual quality for your users. easy, giving you all the development tools you need. Get Content Online Faster Reach Every Device and Every Browser Bitmovin’s containerized encoding architecture makes it the By encoding into adaptive streaming formats - MPEG-DASH fastest encoding service on the market (up to 100x realtime). and HLS - you can ensure that your videos will play on every For broadcasters and news agencies, time-sensitive videos browser and in every device, in standard, as well as 360° and can be made public within seconds, securing the first to air VR formats. advantage and the lion’s share of the ad revenue. A powerful API built for developers Bitmovin API has clients for all the major languages, comprehensive documentation, tutorials and examples so you can kick off your first encoding in just a few minutes. Latest Codec Support Server-Side Ad Insertion Comprehensive support for HEVC, VP9, AV1 Increase your ad revenue by pushing your ads for High definition video everywhere past Ad Blocking software Live Streaming Multi-Codec Streaming Live-to-VoD for instant playback and highlight Save bandwidth by dynamically selecting the clipping plus HEVC, VP9, AV1, DRM, 60FPS, 4K optimal codec Advanced Encoding Settings DRM Support & Integration Finetune the encoding settings to get exactly MPEG CENC with Widevine, PrimeTime, the configuration you need PlayReady. FairPlay for HLS. Integrations with multiple DRM providers. JS Contact [email protected] for a demonstration or trial Horizontal scalability multiplies video encoding performance Take a video, split it into chunks, and encode segments simultaneously across multiple instances. With this approach a video can be encoded with speeds of up to 100x real-time and it also enables real-time live streaming with multiple renditions and sophisticated codecs such as VP9, HEVC and AV1 Encoding speeds of up to 100x real-time MPEG-DASH, HLS, Smooth Streaming Encoding & packaging fMP4 (H.264 or HEVC) with HLS SSAI with YoSpace and DFP World class support SSAI with ID3 tags, HLS cue points, SCTE-35 and EMSG Containers: MP4, MPEG-TS, WebM, CFF Highly customizable encoder Live HEVC, VP9, AV1, DRM, 60FPS, 4K Fast and easy integration and setup Live-to-VoD Zero downtime deployments and upgrades MPEG-CENC DRM & Offline DRM support Actively maintained API clients for all major languages Widevine, PlayReady, PrimeTime, Marlin and Fairplay Comprehensive, actively maintained documentation Multi-Cloud (AWS, Google, Azure) Codecs: H264/AVC, H265/HEVC, VP9, AV1, AAC, AC3, Inputs & Outputs: AWS S3, GCS, Azure, FTP, SFTP, E-AC3, MP3, Vorbis HTTP,Aspera, Scality, Swift, Rackspace, Cloudian, IBM Subtitles and Closed Captions: WebVTT, SRT, TTML, Bluemix, S3 compatible protocols SMPTE-TT, EBU-TT, DFXP, 608/708, SCC US: +1 650-458-5453 EU: +43 463-203-014 Over 50% of today’s online video relies on technology that we developed As the video industry evolves, so does the technology that drives it. Bitmovin has been a first mover in almost every significant development in online video, from building and deploying the world’s first (and fastest) Pioneers of adaptive commercial adaptive streaming (MPEG-DASH/HLS) HTML5 Player, to streaming technology being the first to achieve 100x realtime encoding speeds in the cloud. Bitmovin provides HEVC as well as VP9 live streaming with 60FPS and 4K resolution, and built the first containerized video encoding solution with There is no company in Docker and Kubernetes. the world better qualified Bitmovin products are completely in-house developed, easy and fast to to help you stream video! integrate and highly customizable. In combination with our great support, documentation and SLAs, this is a true enterprise offering. To find out more about Bitmovin’s video infrastructure solutions, or about any individual products, contact [email protected], or visit our website: bitmovin.com “A trusted partner for Integrators, Solution Providers and Content Providers alike.“ For more information, visit our website at bitmovin.com or email: [email protected] Bitmovin, Inc. Headquarters 301 Howard Street, Suite 1800 | San Francisco | CA 94105 | USA | +1 650 4585453 Bitmovin also has offices in New York, Chicago, Seattle, Hong Kong, Austria, Sao Paulo, and the Netherlands, as well as sales operations in countries all around the world..
Recommended publications
  • On Audio-Visual File Formats
    On Audio-Visual File Formats Summary • digital audio and digital video • container, codec, raw data • different formats for different purposes Reto Kromer • AV Preservation by reto.ch • audio-visual data transformations Film Preservation and Restoration Hyderabad, India 8–15 December 2019 1 2 Digital Audio • sampling Digital Audio • quantisation 3 4 Sampling • 44.1 kHz • 48 kHz • 96 kHz • 192 kHz digitisation = sampling + quantisation 5 6 Quantisation • 16 bit (216 = 65 536) • 24 bit (224 = 16 777 216) • 32 bit (232 = 4 294 967 296) Digital Video 7 8 Digital Video Resolution • resolution • SD 480i / SD 576i • bit depth • HD 720p / HD 1080i • linear, power, logarithmic • 2K / HD 1080p • colour model • 4K / UHD-1 • chroma subsampling • 8K / UHD-2 • illuminant 9 10 Bit Depth Linear, Power, Logarithmic • 8 bit (28 = 256) «medium grey» • 10 bit (210 = 1 024) • linear: 18% • 12 bit (212 = 4 096) • power: 50% • 16 bit (216 = 65 536) • logarithmic: 50% • 24 bit (224 = 16 777 216) 11 12 Colour Model • XYZ, L*a*b* • RGB / R′G′B′ / CMY / C′M′Y′ • Y′IQ / Y′UV / Y′DBDR • Y′CBCR / Y′COCG • Y′PBPR 13 14 15 16 17 18 RGB24 00000000 11111111 00000000 00000000 00000000 00000000 11111111 00000000 00000000 00000000 00000000 11111111 00000000 11111111 11111111 11111111 11111111 00000000 11111111 11111111 11111111 11111111 00000000 11111111 19 20 Compression Uncompressed • uncompressed + data simpler to process • lossless compression + software runs faster • lossy compression – bigger files • chroma subsampling – slower writing, transmission and reading • born
    [Show full text]
  • Amphion Video Codecs in an AI World
    Video Codecs In An AI World Dr Doug Ridge Amphion Semiconductor The Proliferance of Video in Networks • Video produces huge volumes of data • According to Cisco “By 2021 video will make up 82% of network traffic” • Equals 3.3 zetabytes of data annually • 3.3 x 1021 bytes • 3.3 billion terabytes AI Engines Overview • Example AI network types include Artificial Neural Networks, Spiking Neural Networks and Self-Organizing Feature Maps • Learning and processing are automated • Processing • AI engines designed for processing huge amounts of data quickly • High degree of parallelism • Much greater performance and significantly lower power than CPU/GPU solutions • Learning and Inference • AI ‘learns’ from masses of data presented • Data presented as Input-Desired Output or as unmarked input for self-organization • AI network can start processing once initial training takes place Typical Applications of AI • Reduce data to be sorted manually • Example application in analysis of mammograms • 99% reduction in images send for analysis by specialist • Reduction in workload resulted in huge reduction in wrong diagnoses • Aid in decision making • Example application in traffic monitoring • Identify areas of interest in imagery to focus attention • No definitive decision made by AI engine • Perform decision making independently • Example application in security video surveillance • Alerts and alarms triggered by AI analysis of behaviours in imagery • Reduction in false alarms and more attention paid to alerts by security staff Typical Video Surveillance
    [Show full text]
  • Encoding H.264 Video for Streaming and Progressive Download
    W4: KEY ENCODING SKILLS, TECHNOLOGIES TECHNIQUES STREAMING MEDIA EAST - 2019 Jan Ozer www.streaminglearningcenter.com [email protected]/ 276-235-8542 @janozer Agenda • Introduction • Lesson 5: How to build encoding • Lesson 1: Delivering to Computers, ladder with objective quality metrics Mobile, OTT, and Smart TVs • Lesson 6: Current status of CMAF • Lesson 2: Codec review • Lesson 7: Delivering with dynamic • Lesson 3: Delivering HEVC over and static packaging HLS • Lesson 4: Per-title encoding Lesson 1: Delivering to Computers, Mobile, OTT, and Smart TVs • Computers • Mobile • OTT • Smart TVs Choosing an ABR Format for Computers • Can be DASH or HLS • Factors • Off-the-shelf player vendor (JW Player, Bitmovin, THEOPlayer, etc.) • Encoding/transcoding vendor Choosing an ABR Format for iOS • Native support (playback in the browser) • HTTP Live Streaming • Playback via an app • Any, including DASH, Smooth, HDS or RTMP Dynamic Streaming iOS Media Support Native App Codecs H.264 (High, Level 4.2), HEVC Any (Main10, Level 5 high) ABR formats HLS Any DRM FairPlay Any Captions CEA-608/708, WebVTT, IMSC1 Any HDR HDR10, DolbyVision ? http://bit.ly/hls_spec_2017 iOS Encoding Ladders H.264 HEVC http://bit.ly/hls_spec_2017 HEVC Hardware Support - iOS 3 % bit.ly/mobile_HEVC http://bit.ly/glob_med_2019 Android: Codec and ABR Format Support Codecs ABR VP8 (2.3+) • Multiple codecs and ABR H.264 (3+) HLS (3+) technologies • Serious cautions about HLS • DASH now close to 97% • HEVC VP9 (4.4+) DASH 4.4+ Via MSE • Main Profile Level 3 – mobile HEVC (5+)
    [Show full text]
  • IP-Soc Shanghai 2017 ALLEGRO Presentation FINAL
    Building an Area-optimized Multi-format Video Encoder IP Tomi Jalonen VP Sales www.allegrodvt.com Allegro DVT Founded in 2003 Privately owned, based in Grenoble (France) Two product lines: 1) Industry de-facto standard video compliance streams Decoder syntax, performance and error resilience streams for H.264|MVC, H.265/SHVC, VP9, AVS2 and AV1 System compliance streams 2) Leading semiconductor video IP Multi-format encoder IP for H.264, H.265, VP9, JPEG Multi-format decoder IP for H.264, H.265, VP9, JPEG WiGig IEEE 802.11ad WDE CODEC IP 2 Evolution of Video Coding Standards International standards defined by standardization bodies such as ITU-T and ISO/IEC H.261 (1990) MPEG-1 (1993) H.262 / MPEG-2 (1995) H.263 (1996) MPEG-4 Part 2 (1999) H.264 / AVC / MPEG-4 Part 10 (2003) H.265 / HEVC (2013) Future Video Coding (“FVC”) MPEG and ISO "Preliminary Joint Call for Evidence on Video Compression with Capability beyond HEVC.” (202?) Incremental improvements of transform-based & motion- compensated hybrid video coding schemes to meet the ever increasing resolution and frame rate requirements 3 Regional Video Standards SMPTE standards in the US VC-1 (2006) VC-2 (2008) China Information Industry Department standards AVS (2005) AVS+ (2012) AVS2.0 (2016) 4 Proprietary Video Formats Sorenson Spark On2 VP6, VP7 RealVideo DivX Popular in the past partly due to technical merits but mainly due to more suitable licensing schemes to a given application than standard video video formats with their patent royalties. 5 Royalty-free Video Formats Xiph.org Foundation
    [Show full text]
  • PVQ Applied Outside of Daala (IETF 97 Draft)
    PVQ Applied outside of Daala (IETF 97 Draft) Yushin Cho Mozilla Corporation November, 2016 Introduction ● Perceptual Vector Quantization (PVQ) – Proposed as a quantization and coefficient coding tool for NETVC – Originally developed for the Daala video codec – Does a gain-shape coding of transform coefficients ● The most distinguishing idea of PVQ is the way it references a predictor. – PVQ does not subtract the predictor from the input to produce a residual Mozilla Corporation 2 Integrating PVQ into AV1 ● Introduction of a transformed predictors both in encoder and decoder – Because PVQ references the predictor in the transform domain, instead of using a pixel-domain residual as in traditional scalar quantization ● Activity masking, the major benefit of PVQ, is not enabled yet – Encoding RDO is solely based on PSNR Mozilla Corporation 3 Traditional Architecture Input X residue Subtraction Transform T signal R predictor P + decoded X Inverse Inverse Scalar decoded R Transform Quantizer Quantizer Coefficient bitstream of Coder coded T(X) Mozilla Corporation 4 AV1 with PVQ Input X Transform T T(X) PVQ Quantizer PVQ Coefficient predictor P Transform T T(X) Coder PVQ Inverse Quantizer Inverse dequantized bitstream of decoded X Transform T(X) coded T(X) Mozilla Corporation 5 Coding Gain Change Metric AV1 --> AV1 with PVQ PSNR Y -0.17 PSNR-HVS 0.27 SSIM 0.93 MS-SSIM 0.14 CIEDE2000 -0.28 ● For the IETF test sequence set, "objective-1-fast". ● IETF and AOM for high latency encoding options are used. Mozilla Corporation 6 Speed ● Increase in total encoding time due to PVQ's search for best codepoint – PVQ's time complexity is close to O(n*n) for n coefficients, while scalar quantization has O(n) ● Compared to Daala, the search space for a RDO decision in AV1 is far larger – For the 1st frame of grandma_qcif (176x144) in intra frame mode, Daala calls PVQ 3843 times, while AV1 calls 632,520 times, that is ~165x.
    [Show full text]
  • Bitmovin's “Video Developer Report 2018,”
    MPEG MPEG VAST VAST HLS HLS DASH DASH H.264 H.264 AV1 AV1 HLS NATIVE NATIVE CMAF CMAF RTMP RTMP VP9 VP9 ANDROID ANDROID ROKU ROKU HTML5 HTML5 Video Developer MPEG VAST4.0 MPEG VAST4.0 HLS HLS DASH DASH Report 2018 H.264 H.264 AV1 AV1 NATIVE NATIVE CMAF CMAF ROKU RTMP ROKU RTMP VAST4.0 VAST4.0 VP9 VP9 ANDROID ANDROID HTML5 HTML5 DRM DRM MPEG MPEG VAST VAST DASH DASH AV1 HLS AV1 HLS NATIVE NATIVE H.264 H.264 CMAF CMAF RTMP RTMP VP9 VP9 ANDROID ANDROID ROKU ROKU MPEG VAST4.0 MPEG VAST4.0 HLS HLS DASH DASH H.264 H.264 AV1 AV1 NATIVE NATIVE CMAF CMAF ROKU ROKU Welcome to the 2018 Video Developer Report! First and foremost, I’d like to thank everyone for making the 2018 Video Developer Report possible! In its second year the report is wider both in scope and reach. With 456 survey submissions from over 67 countries, the report aims to provide a snapshot into the state of video technology in 2018, as well as a vision into what will be important in the next 12 months. This report would not be possible without the great support and participation of the video developer community. Thank you for your dedication to figuring it out. To making streaming video work despite the challenges of limited bandwidth and a fragmented consumer device landscape. We hope this report provides you with insights into what your peers are working on and the pain points that we are all experiencing. We have already learned a lot and are looking forward to the 2019 Video Developer Survey a year from now! Best Regards, StefanStefan Lederer Lederer CEO, Bitmovin Page 1 Key findings In 2018 H.264/AVC dominates video codec usage globally, used by 92% of developers in the survey.
    [Show full text]
  • CALIFORNIA STATE UNIVERSITY, NORTHRIDGE Optimized AV1 Inter
    CALIFORNIA STATE UNIVERSITY, NORTHRIDGE Optimized AV1 Inter Prediction using Binary classification techniques A graduate project submitted in partial fulfillment of the requirements for the degree of Master of Science in Software Engineering by Alex Kit Romero May 2020 The graduate project of Alex Kit Romero is approved: ____________________________________ ____________ Dr. Katya Mkrtchyan Date ____________________________________ ____________ Dr. Kyle Dewey Date ____________________________________ ____________ Dr. John J. Noga, Chair Date California State University, Northridge ii Dedication This project is dedicated to all of the Computer Science professors that I have come in contact with other the years who have inspired and encouraged me to pursue a career in computer science. The words and wisdom of these professors are what pushed me to try harder and accomplish more than I ever thought possible. I would like to give a big thanks to the open source community and my fellow cohort of computer science co-workers for always being there with answers to my numerous questions and inquiries. Without their guidance and expertise, I could not have been successful. Lastly, I would like to thank my friends and family who have supported and uplifted me throughout the years. Thank you for believing in me and always telling me to never give up. iii Table of Contents Signature Page ................................................................................................................................ ii Dedication .....................................................................................................................................
    [Show full text]
  • Download the Inspector Product Sheet (Pdf)
    INSPECTOR Because your lab only has so many people... SSIMPLUS VOD Monitor Inspector is the only video quality measurement software with the algorithm trusted by Hollywood to determine the best possible configuration for R&D groups, engineers and architects who set up VOD encoding and processing workflows or make purchasing recommendations. Video professionals can evaluate more encoders and transcoders with the fastest and most comprehensive solution in the business. From the start of your workflow to delivering to consumer endpoints, VOD Monitor Inspector is here to help ensure every step along the way works flawlessly. Easy-to-use tools provide: A/B testing for encoding configurations and purchasing decisions Sandbox environment for encoder or transcoder output troubleshooting “The SSIMPLUS score developed Creation of custom templates to identify best practices for specific content libraries by SSIMWAVE represents a Configurable automation to save time and eliminate manual QA/QC generational breakthrough in Side-by-side visual inspector to subjectively assess degradations the video industry.” Perceptual quality maps that provide pixel level graphic visualization –The Television Academy of content impairments Allows you to optimize network performance and improve quality Our Emmy Award-winning SSIMPLUS™ score mimics the accuracy of 100,000 human eyes. Know the score when it YOU CAN HOW OUR SEE THE SOFTWARE SEES DEGRADATION THE DEGRADATION comes to video quality NARROW IT DOWN TO THE The SSIMPLUS score is the most accurate measurement PIXEL LEVEL representing how end-viewers perceive video quality. Our score can tell exactly where video quality degrades. 18 34 59 72 87 10 20 30 40 50 60 70 80 90 100 BAD POOR FAIR GOOD EXCELLENT Helping your workflow, work SSIMPLUS VOD Monitor Inspector helps ensure your video infrastructure is not negatively impacting content anywhere in your workflow.
    [Show full text]
  • AVC, HEVC, VP9, AVS2 Or AV1? — a Comparative Study of State-Of-The-Art Video Encoders on 4K Videos
    AVC, HEVC, VP9, AVS2 or AV1? | A Comparative Study of State-of-the-art Video Encoders on 4K Videos Zhuoran Li, Zhengfang Duanmu, Wentao Liu, and Zhou Wang University of Waterloo, Waterloo, ON N2L 3G1, Canada fz777li,zduanmu,w238liu,[email protected] Abstract. 4K, ultra high-definition (UHD), and higher resolution video contents have become increasingly popular recently. The largely increased data rate casts great challenges to video compression and communication technologies. Emerging video coding methods are claimed to achieve su- perior performance for high-resolution video content, but thorough and independent validations are lacking. In this study, we carry out an in- dependent and so far the most comprehensive subjective testing and performance evaluation on videos of diverse resolutions, bit rates and content variations, and compressed by popular and emerging video cod- ing methods including H.264/AVC, H.265/HEVC, VP9, AVS2 and AV1. Our statistical analysis derived from a total of more than 36,000 raw sub- jective ratings on 1,200 test videos suggests that significant improvement in terms of rate-quality performance against the AVC encoder has been achieved by state-of-the-art encoders, and such improvement is increas- ingly manifest with the increase of resolution. Furthermore, we evaluate state-of-the-art objective video quality assessment models, and our re- sults show that the SSIMplus measure performs the best in predicting 4K subjective video quality. The database will be made available online to the public to facilitate future video encoding and video quality research. Keywords: Video compression, quality-of-experience, subjective qual- ity assessment, objective quality assessment, 4K video, ultra-high-definition (UHD), video coding standard 1 Introduction 4K, ultra high-definition (UHD), and higher resolution video contents have en- joyed a remarkable growth in recent years.
    [Show full text]
  • Performance Comparison of AV1, JEM, VP9, and HEVC Encoders
    To be published in Applications of Digital Image Processing XL, edited by Andrew G. Tescher, Proceedings of SPIE Vol. 10396 © 2017 SPIE Performance Comparison of AV1, JEM, VP9, and HEVC Encoders Dan Grois, Tung Nguyen, and Detlev Marpe Video Coding & Analytics Department Fraunhofer Institute for Telecommunications – Heinrich Hertz Institute, Berlin, Germany [email protected],{tung.nguyen,detlev.marpe}@hhi.fraunhofer.de ABSTRACT This work presents a performance evaluation of the current status of two distinct lines of development in future video coding technology: the so-called AV1 video codec of the industry-driven Alliance for Open Media (AOM) and the Joint Exploration Test Model (JEM), as developed and studied by the Joint Video Exploration Team (JVET) on Future Video Coding of ITU-T VCEG and ISO/IEC MPEG. As a reference, this study also includes reference encoders of the respective starting points of development, as given by the first encoder release of AV1/VP9 for the AOM-driven technology, and the HM reference encoder of the HEVC standard for the JVET activities. For a large variety of video sources ranging from UHD over HD to 360° content, the compression capability of the different video coding technology has been evaluated by using a Random Access setting along with the JVET common test conditions. As an outcome of this study, it was observed that the latest AV1 release achieved average bit-rate savings of ~17% relative to VP9 at the expense of a factor of ~117 in encoder run time. On the other hand, the latest JEM release provides an average bit-rate saving of ~30% relative to HM with a factor of ~10.5 in encoder run time.
    [Show full text]
  • Why “Not- Compressing” Simply Doesn't Make Sens ?
    WHY “NOT- COMPRESSING” SIMPLY DOESN’T MAKE SENS ? Confidential IMAGES AND VIDEOS ARE LIKE SPONGES It seems to be a solid. But what happens when you squeeze it? It gets smaller! Why? If you look closely at the sponge, you will see that it has lots of holes in it. The sponge is made up of a mixture of solid and gas. When you squeeze it, the solid part changes it shape, but stays the same size. The gas in the holes gets smaller, so the entire sponge takes up less space. Confidential 2 IMAGES AND VIDEOS ARE LIKE SPONGES There is a lot of data that are not bringing any information to our human eyes, and we can remove it. It does not make sense to transport, store uncompressed images/videos. It is adding data that have an undeniable cost and that are not bringing any additional valuable information to the viewers. Confidential 3 A 4K TV SHOW WITHOUT ANY CODEC ▪ 60 MINUTES STORAGE: 4478.85 GB ▪ STREAMING: 9.953 Gbit per sec Confidential 4 IMAGES AND VIDEOS ARE LIKE SPONGES Remove Remove Remove Remove Temporal redundancy Spatial redundancy Visual redundancy Coding redundancy (interframe prediction,..) (transforms,..) (quantization,…) (entropy coding,…) Confidential 5 WHAT IS A CODEC? Short for COder & DECoder “A codec is a device or computer program for encoding or decoding a digital data stream or signal.” Note : ▪ It does not (necessarily) define quality ▪ It does not define transport / container format method. Confidential 6 WHAT IS A CODEC? Quality, Latency, Complexity, Bandwidth depend on how the actual algorithms are processing the content.
    [Show full text]
  • ENCODING CONTENT a Codecistheencoder-Decoder Device Used to Compress Thedataa Video/Audio in Stream
    ENCODING CONTENT APPLICATION NOTES Agree Terms What is a codec and why are there so many? Why does Hippo�zer have to encode content? How does Hippo�zer handle encoded content? Terms and Defini�ons: A Codec is the Encoder-Decoder device used to compress the data in a video/audio stream. VIDEO FOOTAGE VIDEO CODEC VIDEO CODEC A Container is a file that allows audio, video and data files to be stored within it. ORIGINAL • PREPARE • DELIVER • PREPARE FOOTAGE .Mov - Proprietary file format used by Apple’s quick �me framework. .AVI - Microso� proprietary file format .mp4 DESIGN ENCODING DECODING PLAYBACK A Video Codec encode / decode video (as opposed to audio) H.265 / MPEG-H HEVC -> Streaming, Blu-ray ORIGINAL SOUND Apple ProRes -> Video Produc�on AV1 -> HTML5 Video AUDIO CODEC AUDIO CODEC SOUND READ MORE ABOUT GREEN HIPPO’S FLEXRES CODEC HERE www.green-hippo.com/hippo�zer-key-features/flexres-codec/ NOT ALL CODECS ARE CREATED EQUAL: There is no easy answer to what the best codec is: HIGHQUALITY HIGHQUALITY UNC AUTOSHOWS LOSSLESS YOUTUBE MEDIA SERVERS FLEXRES QUALITY LIVE STREAMING EVENTS FLEXRES DECODE DIGITAL SIGNAGE SMALL FILES DECODE PERFORMANCE SMALL FILES EFFICIENCY (BETTER COMPRESSION) EFFICIENCY • PREPARE • DELIVER • PREPARE FlexRes Tools is a free suite of plugins and u�li�es to streamline content crea�on workflows. How does Hippo�zer encode and handle Media? Flexibility is key for a media server. One show may need 8K+ playback while the next may require perfect DESIGN 4:4:4 colour and uncompressed playback. FlexRes is a suite of codecs that features the flexibility to do Hippo�zer has a built-in transcoder from most common formats.
    [Show full text]