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Vicodeo™ - Video Decoding

Accelerated video decoding solution for managed environments (.NET and Java).

Our library features accelerated video decoding performance for various environments and needs, from high-quality/resolution displays to streaming content at low-quality and resolution.

Capable of processing 1080p (@30 FPS, Full HD, 1920x1080 pixels) streams faster than real-time, even on low-end platforms, it is possible to handle multiple streams on the same platform, or apply image filters/algorithms on video output.

The library is pure software implementation (not a DirectShow filter!), and contains accelerated color space conversion routines to handle YUV 4:2:0 sampling to RGB.

For more information, please contact us at: support@hoopoe-cloud.com.
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• Applications
• Features
• Package Contents
• Requirements

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Applications

High-Quality film display (Full HD, 1080p) Security/surveillance Live streaming Video conferencing Video processing Remote sensing

-> YUV to RGB color space conversion. Images were decoded from the official trailer of "Big Buck Bunny" movie. Licensed under Creative Commons Attribution 3.0. © copyright Blender Foundation | www.bigbuckbunny.org

Features

• Accelerated video decoding
• Faster than real-time decoding for 1080p streams, even on low-end platforms
• Codec support: H.264, MPEG-1/2/4, VC-1
• Support for progressive and interlaced streams
• Color space conversion (YUV 4:2:0 to RGB)
• Support for different ITU.R (BT.709, BT.601) color matrices
• Optional low-level interface for greater decoding flexibility
• Integrated parser for elementary/transport streams and video packets
• Simple and intuitive API for easy integration
• Transparent integration with DirectX or OpenGL
• Apply image filters or further processing directly on frame buffer (YUV plane or RGB)
• Selective automatic output to YUV or RGB formats
• Support for immediate presentation of video packets (real-time presentation without delayed)

Package Contents

• Library binaries
• Full API documentation
• Sample decoder implementation

Requirements

• Microsoft Windows Operating System:
  
  • Desktop: Windows XP SP2 and above
  • Server: Windows 2003 and above
  • Embedded: Windows XP Embedded and above
• NVIDIA CUDA compatible GPU