Noise shaping for direct binary search image halftoning

Among image halftoning algorithms, direct binary search (DBS) minimizes the total squared perceived error instead of using heuristic approaches. Therefore, it can generate halftone output with the best quality. The limitation of DBS is that its halftone pattern is controlled by the autocorrelation filter, which corresponds to both the human visual system and the printer model. Because of the low-pass characteristics of the filter, DBS can only generate blue-noise-like halftone pattern and the only variation is the clustered-dot algorithm proposed in 2013. We use the results of theoretical bounds to show that halftone patterns in DBS can be controlled in both frequency and spatial domains through an approach called “noise shaping.” This approach is achieved through an added term to the filtered error in DBS. We also show that DBS clustered-dot halftoning is a special case of this noise-shaping approach. Experimental results show that both the spatial-domain and frequency-domain characteristics of the generated halftone pattern can be manipulated freely using this approach.