Damera - Venkata and Evans : Vector Color Error Diffusion

Traditional error di usion halftoning is a high quality method for producing binary images from digital grayscale images. Error di usion shapes the quantization noise power into the high frequency regions where the human eye is the least sensitive. Error di usion may be extended to color images by using error lters with matrix-valued coe cients to take into account the correlation among color planes. For vector color error di usion, we propose three contributions. First, we analyze vector color error di usion based on a new matrix gain model for the quantizer, which linearizes vector error di usion. The model predicts key characteristics of color error di usion, esp. image sharpening and noise shaping. The proposed model includes linear gain models for the quantizer by Ardalan and Paulos and by Kite, Evans, and Bovik as special cases. Second, based on our model, we optimize the noise shaping behavior of color error di usion by designing error lters that are optimum with respect to any given linear spatially-invariant model of the human visual system. Our approach allows the error lter to have matrix-valued coe cients and di use quantization error across color channels in an opponent color representation. Thus, the noise is shaped into frequency regions of reduced human color sensitivity. To obtain the optimal lter, we derive a matrix version of the Yule-Walker equations which we solve by using a gradient descent algorithm. Finally, we show that the vector error lter has a parallel implementation as a polyphase lterbank.