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Pingshan Li

Publications and source records attributed to Pingshan Li.

2 recordsLinked to original sources

Tone-dependent error diffusion.

We present an enhanced error diffusion halftoning algorithm for which the filter weights and the quantizer thresholds vary depending on input pixel value. The weights and thresholds are optimized based on a human visual system model. Based on an analysis of the edge behavior, a tone dependent threshold is designed to reduce edge effects and start-up delay. We also propose an error diffusion system with parallel scan that uses variable weight locations to reduce worms.

Algorithms↗

Clustered-minority-pixel error diffusion.

We present a clustered-minority-pixel error-diffusion halftoning algorithm for which the quantizer threshold is modified on the basis of the past output and a dot activation map. Dot area, dot shape, and dot distribution are more controllable than with other clustered-dot halftone algorithms such as Levien's algorithm. This method also effectively reduces structured mazelike artifacts in midtones that occur in Levien's algorithm. The dot distribution is further improved by using different error-diffusion weights for different input gray levels.

Journal Article↗