Optimal Black Separation Signal Prediction with Luminance for Color Printing Image Coding

Abstract

An Optimal black separation signal prediction method in the mean square error (MSE) sense is presented for color printing image coding. In this method, a prediction error signal (eK) is defined as the difference between an actual black separation k signal and a predicted k signal with luminance. In this prediction, the k signal predictor is statistically designed under a criterion of minimization of the mean square prediction error, so that the predicted value is equal to the conditional expected value of k for each luminace level. By the cmy-YIQ conversion and the use of an eK signal instead of a k signal, the spectral redundancy among the c, m, y and k signals is removed, and more efficient coding is expected. In the coding scheme, these Y, I, Q and eK signals are spatially coded separately. The simulation results show that YIQeKDPCM coding applying this prediction method is superior to conventional YIQkDPCM coding in SNR for the k signal.