Bring out the Best in Pixels Video Pipe in Intel Processor Graphics

Transcription

1 Bring out the Best in Pixels Video Pipe in Intel Processor Graphics Victor H. S. Ha and Yi-Jen Chiu Graphics Architecture, Intel Corp.

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3 Contents Intel Processor Graphics Video Processing Pipe Video Processing Modules Control Panel Adaptive Processing Summary Q&A 3

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5 Command Streamers Vertex Processing Rasterize Multi-Format Codec Media Processing Instruction Cache EU EU EU Array of Unified Execution Units EU EU EU Video Quality Engine Display Media Sampler Texture Sampler Pixel Ops 4 th Generation Intel Core Microprocessor, built on 22 nm process technology Next Generation Intel HD Graphics with Microsoft * DirectX * 11.1, OpenGL * 4.0, OpenCL* 1.2 support Three Simultaneous Display, HDMI, DisplayPort *, with high-resolution up to 4Kx2K Significant 3D and Media performance improvement 5

6 SD, FHD, UHD 4K Interlaced / Progressive Chroma Format: 420/422/444 JPG, MPG, H.264, VC1 WiFi WebCam BT Ethernet/LAN HDD USB DVD/BD Source Format, Content, Quality Intel Graphics Media Processing Network Mobility VGA Display Port DVI/HDMI WiDi 6

7 Bring out the Best in Pixels Multi-format Codec Decode MPEG2 / VC1 AVC SVC MVC JPEG / MJPEG Denoise Deinterlace Contrast Saturation Skin-tone Gamut Color Correction Stabilization VQE Media Sampler Scaling Sharpness 7

8 Contents Intel Processor Graphics Video Processing Pipe Video Processing Modules Control Panel Adaptive Processing Summary Q&A 8

9 Multi-Format Codec Video Decode and Encode High Performance Parallel Engine Video Quality Engine Video Processing Color Processing Command Streamers Front-End Thread Dispatch/Management Multi - format Codec Media FrontEnd Video Processing Pipeline VQE Introducing Video Quality Engine 3D Geometry Processing EU Array of Execution Units EU EU EU Media Samplers Texture Samplers Media Accelerators $L3 Cache Rasterizer EU EU EU EU Pixel Ops Media Optimized Execution Units 9

10 Video Processing Pipe Dedicated video processing on newly designed Video Quality Engine (VQE) Support for an extensive suite of functions for higher quality video at lower power Denoise Deinterlace Skin-tone Gamut Compression Contrast Saturation ProcAmp Sharpness Scaler Image Stabilization Gamut Expansion CSC 10

11 Contents Intel Processor Graphics Video Processing Pipe Video Processing Modules Control Panel Adaptive Processing Summary Q&A 11

12 De-noise Spatial and Temporal De-noise Filter Global noise level measurement Content-adaptive spatiotemporal filtering of noise Motion history-based blending of spatial and temporal filter results Noisy Images Clean Images Block Interface Input: YCbCr 420/422 Output: YCbCr 420/422 12

13 De-interlace Convert interlaced contents to progressive format Edge-adaptive Spatial Interpolation result + Motion-compensated Interpolation result Motion-adaptive Blending with Temporal Filtering results based on Spatial Temporal Motion Measure (STMM) Detection of most common cadences Chroma Upsampling from 420 to

14 Skin-tone Processing Per-pixel Enhancement of Skin-tone Pixels Reproduce the natural skin colors on the display screen Skin Tone Detection identifies pixels with skin-like colors with per-pixel indicator Skin Tone Enhancement modifies the Saturation and Hue of the skin-tone pixels Original Input Skin-tone Definition Skin-tone Detection Skin-tone Enhancement Skin-tone Indicator Skin-tone Enhanced Output Block Interface Input: YCbCr444 Output: YCbCr444 with modified CbCr components; Per-pixel skin tone indicator 14

15 Contrast Enhancement Automatic Contrast Enhancement: Per-pixel mapping of luma to enhance contrast 1. Histogram of luma Y pixel values is generated for the input video frame 2. Piece-Wise Linear Function (PWLF) is generated from luma histogram 3. Pixel values are modified according to the PWLF Input Image Histogram Computation PWLF Mapping Enhanced Image Block Interface Input: YCbCr 444 Output: YCbCr 444 with modified Y 15

16 Saturation Enhancement Per-Pixel Saturation Enhancement Utilize 6 basic colors as primaries/anchors (Red, Green, Blue, Magenta, Yellow, Cyan) Adjust colorfulness (saturation) of pixels while maintaining their color (hue) Input Image Saturation Enhanced Image Block Interface Input: YCbCr 444 Output: YCbCr 444 with modified CbCr components 16

17 Color Correction Display proper colors on display screen 1. Inverse gamma correction via PWLF 2. 3x3 matrix multiplication with input/output offset 3. Forward gamma correction via PWLF Input Image Color Corrected Image Block Interface Input: RGB Output: RGB 17

18 Image Stabilization Stabilize shaky video contents captured by handheld camera devices Usage models Real-time playback: Watch real-time playback of video streams Offline processing: Stabilize shaky video and save/transmit for video sharing Block Interface Input: YCbCr 420 Output: YCbCr

19 Scaler Adaptive Video Scaler Advanced scaling method for adaptive scaling mode Content-adaptive per-pixel blending of polyphase filtering and bilinear filtering reduces ringing Programmable coefficient tables available for Y / CbCr channels in horizontal and vertical directions Support for up to 16:1 downscaling and max output picture size of 16Kx16K for YUV420/422/444/RGB input picture 19

20 Sharpness Enhancement Enhancement of Image Sharpness and Details Content adaptive spatial filtering applied to luma channel User control of sharpness enhancement strength = [0, 63] Adaptive to Skin Tone Pixels Skin tone information is utilized Enhance detail information without over-sharpening of the skin regions Interface Input: YCbCr 444 Output: YCbCr

21 Contents Intel Processor Graphics Video Processing Pipe Video Processing Modules Control Panel Adaptive Processing Summary Q&A 21

22 Control Panel Standard Color Correction Brightness Contrast Hue Saturation 22

23 Control Panel Input Range Limited Full Total Color Correction Saturation Enhancement Adjustment = [0, 255] 23

24 Control Panel Sharpness Driver Custom Settings = [0, 64] Skin Tone Enhancement On = [0, 9] Off 24

25 Control Panel Noise Reduction Luma only = [0, 64] Luma and Chroma = [0, 64] Contrast Enhancement On/Off Film Mode Detection On/Off 25

26 Contents Intel Processor Graphics Video Processing Pipe Control Panel Video Processing Modules Adaptive Processing Summary Q&A 26

27 Hardware Statistics Statistics are gathered on Per-block (16x4) basis for encoder stats Per-frame basis for other stats 16 bytes of encoder statistics data for per-block statistics is available Temporal Variances De-noise: Sum of block noise estimates and Number of blocks per frame A variety of per-frame data is stored in a linear surface Skin-tone: Ymax = Max luma value, Ymin = Min luma value, Counter = Number of skin pixels Contrast: Luma histogram with 256 bins and 24-bits per bin Gamut Compression: Sum of distances of out-of-gamut-range pixels clipped to 32 bits, Number of out-of-gamut-range pixels in 29 bits 27

28 Adaptive Processing & Control The goal of adaptive processing is to deliver optimized video experience Hardware statistics and adaptive control logic allow end-to-end optimization and effective sharing of data and information across all processing blocks 28

29 APC Example Noise Level Estimator Global Noise Level Noise Reduction Contrast Enhancement Skin-tone Detection Saturation Enhancement Sharpness Enhancement Global Motion Indicator Motion Detection Brightness Information Luma Histogram Skin-tone Indicator 29

30 Contents Intel Processor Graphics Video Processing Pipe Video Processing Modules Control Panel Adaptive Processing Summary Q&A 30

31 Summary Intel is building Media Solutions for Quality, Power, and Scalable Performance Dedicated HW acceleration for codecs, video and image processing, and analytics Media processing in 4 th Generation Processor Graphics delivers: VQE: A new feature with a full-set of video processing pipe Adaptive Processing & Control for integrated and optimized video pipe behavior Ready for various application scenarios and network/mobility environments Looking Ahead Future generations of Intel media processing will address further HW acceleration in video processing, camera image processing, and perceptual computing/machine vision applications Improvement in power and performance fitted to exciting new form-factors 31

32 Contents Intel Processor Graphics Video Processing Pipe Video Processing Modules Control Panel Adaptive Processing Summary Q&A 32

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