Abstract
Image halftoning converts a high-resolution image to a low-resolution image, e.g., a 24-bit color image to a three-bit color image, for printing and display. Vector error diffusion captures correlation among color planes by using an error filter with matrix-valued coefficients. In optimizing vector error filters, Damera-Venkata and Evans transform the error image into an opponent color space where Euclidean distance has perceptual meaning. This letter evaluates color spaces for vector error filter optimization. In order of increasing quality, the color spaces are YIQ, YUV, opponent (by Poirson and Wandell), and linearized CIELab (by Flohr, Kolpatzik, Balasubramanian, Carrara, Bouman, and Allebach).
Original language | English (US) |
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Pages (from-to) | 93-97 |
Number of pages | 5 |
Journal | IEEE Signal Processing Letters |
Volume | 10 |
Issue number | 4 |
DOIs | |
State | Published - Apr 2003 |
All Science Journal Classification (ASJC) codes
- Signal Processing
- Electrical and Electronic Engineering
- Applied Mathematics