A new algorithm for designing differential pulse code modulation (DPCM) systems is presented for image data compression. When transmitting images over noiseless channels, the distortion between the original and reconstructed images results primarily from quantization noise. This is true when optimal predictor structures are employed. The quantization error becomes severe at low bit rates. This is because of the large quantization error being directly fed back into the predictor and used in subsequent estimation of future pixels. The DPCM scheme developed attempts to balance between nonoptimal predictor designs and significantly reduced feedback effects resulting from quantization errors with the objective of maximizing reconstructed image quality. DPCM system performance using the algorithm is about 2.5 dB greater than that obtained from an optimally designed conventional system. In addition, the algorithm is robust. Thus, the DPCM predictor does not need to be redesigned using exact statistics of the input image data for each image to be transmitted.