Halftoning and Objective Quality Measures for Halftoned Images

1. Halftoning and Objective Quality Measures for Halftoned Images • Halftoning With Pre-Computed Maps • Objective Image Quality Measures

2. Halftoning With Pre-Computed Maps • FM halftoning using threshold matrices • High computational speed • Trade-off between quality of tints and quality of shades • Optimization criteria can not be fulfilled for every tone value • PreCoM • Meet both requirements for all tint levels • Without any loss in speed

3. Pre-Computed Maps, PreCoM • Pre-computed maps, representing every tone value • Halftone volume • Image value as index • No comparison • No information from neighboring pixels

4. Computing the maps • Individually optimized- Full control of the dot pattern for each tone value • Dots in each map maximally dispersed- Avoid graininess • Correlation between adjacent maps- No discontinuity effects

5. Computing the maps • Arbitrary pattern • Gaussian low-pass filter • Locate tightest cluster (maximum) and largest void (minimum) • Remove dot at tightest cluster • Move to largest void • Continue until no further change occur

6. Computing the maps Gaussian low-pass filter Change the width accordingto tone value Circular convolution

7. Creating the locally correlated volume • Optimize • Start with 20% tone value • Add extra dots to create new tone value • Optimize, using the new filter • Continue the iterative process until all maps are created

8. Results PreCoM Error diffusion

9. Summary, PreCoM • Pre-computed maps • Individually optimized • Locally correlated • Tints without graininess • Smoothly varying shades • No loss in computational speed

10. Objective Image Quality Measures • Image quality? • A reproduced image’s resemblance to a digital original • Purpose: evaluate halftone images • Printed • Observed by humans • Evaluate the perceived difference between the printed halftone and the original

11. Requirements • evaluate all kinds of halftones • evaluate halftones for all kinds of printing techniques • judge the quality of real images, not only synthetic test patterns • return measures for several aspects of quality that are well correlated with results from subjective tests An objective quality measure should be able to:

12. The Evaluation model • Use printed images? • Uncontrolled variations • Possible artifacts from scanning • Use models! • Print model • Mechanical dot gain • Optical dot gain • Observer model • Contrast Sensitivity Function

13. Separation of information • Two different types of errors will be mixed: • parts of the original that the halftone could not reproduce • errors introduced by the halftone algorithm • Separate image information: • Halftone carrier • Reconstructed original

14. Reconstructing the original • Extract as much as possible of the original without including the carrier • Use original as reference • Fourier spectrum • Low-pass filter? • No simple band limit! • Use an adaptive filter in the Fourier domain

15. The Adaptive filter • Both magnitude and phase of the frequency components are changed by the halftoning process • The greater the phase difference, the less of the original is described • Take the vector in phase with the halftone that minimizes the Euclidean distance to the original • The remainder of the halftone component is the halftone carrier, describing the halftone characteristics

17. Measuring quality • Reconstructed original • The difference to the original shows information lost in the halftoning process • The capability for the halftone to reproduce the original • Halftone carrier • Extra information introduced into the halftone • May cause disturbances

18. Measuring quality • Radial histogram in the Fourier domain • The average energy in each frequency band

19. Weight functions • Numbers on certain aspects of quality • Use weight functions to emphasize different frequency bands

20. The Quality Measures • Quality measures derived from the error functions: • Low Frequency deviation, LFDev • Loss of Detail, Lod • Loss of Fine Detail, LoFD • Quality measures derived from the carrier functions: • Low Frequency Disturbance, LFD • Medium High Frequency Disturbance, MFD • Very High Frequency Disturbance, VHFD

21. Summary • Method for objective quality measures for halftone images • Evaluates the perceived printed image, using models for the print and the observer • Evaluates both the halftone’s truthfulness to the original and the halftoned characteristics • 6 Different quality measures, emphasizing on different aspects of image quality • Meets the requirements stated initially