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Dithering Algorithm Review
Shereef Shehata
Software Verification Environment Plan (Initial)
• Development of YCbCr input and RGB Input at different
Resolutions: (Ini...
3
Direct YCbCr 4:2:0/4:2:2 input files
Y
Cr
Cb
ARGB8888
Computations
Color
Conversion
YCbCr
Input files
Video
Decode
YCbCr...
4
2D IP Env: conversion for YCbCr 4:2:0
Cr
Cb
2→
2→
Cr
Cb
Y
ARGB8888
Computation
YCrCb
4:2:2
YCrCb
4:4:4
YCbCr->RGB
Cr
Cb
...
5
2D IP Env: conversion for YCbCr 4:2:2
Cr
Cb
2→
2→
Cr
Cb
Y
ARGB8888
Computation
YCrCb
4:2:2
YCrCb
4:4:4
YCbCr->RGB
2D IP ...
Generate RGB reference inputs with 565/555/444
resolutions (optimal)
Master input Image
24 bpp
ARGB8888
Computation
Optima...
Generate RGB reference inputs with 565/555/444
resolutions (Initial)
Master input Image
24 bpp
ARGB8888
Computation
Color ...
Output RGB color dithering for outputs with
565/555/444 resolutions
2D IP Verification Environment
ARGB8888
Computation
Co...
9
RGB 888 Reference image
10
RGB 565 Quantized image
11
RGB 565 Quantized+ Dithered image
12
RGB 555 Quantized image
13
RGB 555 Quantized+dithered image
14
RGB 444 Quantized image
15
RGB 444 Quantized+Dithered image
16
Dithering: Algorithms, Quality Metrics
• Current implementation:
– Current implementation is ordered dither with 8x8 ma...
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Dithering_Algorithm_Review

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Dithering_Algorithm_Review

  1. 1. 1 Dithering Algorithm Review Shereef Shehata
  2. 2. Software Verification Environment Plan (Initial) • Development of YCbCr input and RGB Input at different Resolutions: (Initial target) - Generate RGB reference inputs with 565/555/444 resolutions. - Generate input reference YCbCr data 4:2:2 or 4:2:0 data. - Initial Target: Minimum visual degradation. - Dithering Algorithms for this step does not have to target hardware. - Start with simple dithering algorithms to get environment going. - Statistical optimal color quantization algorithms could be used at a later stage. - Golden reference models can be used to compate visual quality and PSNR. • Output color Dithering for reduced bit width output – The intention of these algorithms is to reduce the bit-width of the output from ARGB8888 to a format that is characterized by a reduced number of bits per channel – Dithering algorithms applied are intended to be implemented on the actual IP hardware. – Dithering Algorithm has to be efficient and hardware implementable. 2
  3. 3. 3 Direct YCbCr 4:2:0/4:2:2 input files Y Cr Cb ARGB8888 Computations Color Conversion YCbCr Input files Video Decode YCbCr 2D IP & Verification Env
  4. 4. 4 2D IP Env: conversion for YCbCr 4:2:0 Cr Cb 2→ 2→ Cr Cb Y ARGB8888 Computation YCrCb 4:2:2 YCrCb 4:4:4 YCbCr->RGB Cr Cb YCrCb 4:2:0 2→2→ 2D IP & Verification Environment
  5. 5. 5 2D IP Env: conversion for YCbCr 4:2:2 Cr Cb 2→ 2→ Cr Cb Y ARGB8888 Computation YCrCb 4:2:2 YCrCb 4:4:4 YCbCr->RGB 2D IP & Verification Environment
  6. 6. Generate RGB reference inputs with 565/555/444 resolutions (optimal) Master input Image 24 bpp ARGB8888 Computation Optimal Statistical Color Quantization 2D IP & Verification Environment Golden Reference Image 565/555/444 format 565/555/444 RGB Convert to ARGB888 Target IP Hardware
  7. 7. Generate RGB reference inputs with 565/555/444 resolutions (Initial) Master input Image 24 bpp ARGB8888 Computation Color Quantization And Dithering (fast algorithms) 2D IP Verification Environment Reference Image 565/555/444 format 565/555/444 RGB Convert to ARGB888 Target IP Hardware
  8. 8. Output RGB color dithering for outputs with 565/555/444 resolutions 2D IP Verification Environment ARGB8888 Computation Color Quantization And Dithering (hardware) Output Image Derived from 565/555/444 format 565/555/444 RGB Target IP Hardware
  9. 9. 9 RGB 888 Reference image
  10. 10. 10 RGB 565 Quantized image
  11. 11. 11 RGB 565 Quantized+ Dithered image
  12. 12. 12 RGB 555 Quantized image
  13. 13. 13 RGB 555 Quantized+dithered image
  14. 14. 14 RGB 444 Quantized image
  15. 15. 15 RGB 444 Quantized+Dithered image
  16. 16. 16 Dithering: Algorithms, Quality Metrics • Current implementation: – Current implementation is ordered dither with 8x8 magic square matrix. • Quality metrics to be used to evaluate dithering algorithms and/or improvement: – PSNR vs. original master 24bpp image + and visual quality. – PSNR vs. Golden optimal color quantized reference image + visual qulity

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