NOVEL NONLINEAR PREDICTIVE IMAGE-CODING ALGORITHM

We present a novel nonlinear predictive image coding scheme in which a relative prediction error is first generated from the current pixel v alue and its predicted value. It is next mapped quantized, coded and t ransmitted. Consequently, a weighting function is introduced into the coding algorithm such that the coding error is adapted by the pixel in tensity and its relative prediction error. Meanwhile, the resulting qu antization step size is smaller in lower contrast areas and larger in higher contrast areas so that the granular noise and the slope overloa d distortion can be efficiently reduced. Our simulation results show t hat on an average, with the proposed scheme, the bit rate is about 0.2 3 bits less than that obtained with differential pulse-code modulation (DPCM), while the peak SNR (PSNR) is about 2.9 dB higher than that wi th DPCM. On the other hand, more coding errors are allocated in less v isible areas where the image intensity and/or contrast are higher. (C) 1997 SPIE and IS&T. [S1017-9909(97)00702-2].