As the primary estimator of the image component compression effects, denoted H0_pMED, we used the memoryless entropy of the component residual image, i.e., of a single-component image consisting of prediction errors calculated as differences between actual and predicted component pixels. The bitrate of the three-component image was estimated as a sum of the estimated bitrates of its three components. The memoryless entropy of a single-component image (a residual image in this case) is , where is the alphabet size and is the probability of occurrence of pixel value in the image. For prediction, we used the nonlinear edge-detecting predictor MED [Eq. (13)],9 which originates from the median adaptive prediction coding of video data:13,14Display Formula
(13)where is the component of the image pixel in column and row and MED is its predicted value. For the top image row, we used as a predictor; for the leftmost column, we used ; and 0 was a predictor for the top left image pixel.