Data Compression Of X-Ray Images By Adaptive Differential Pulse Code Modulation (DPCM) Coding
Leonard A. Lehmann, Albert Macovski · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1981
The intolerance of medical images to error places special demands on data reduction techniques. Quantization in the spatial or transform domains, widely studied in other data compression applications, is irreversible and therefore not applicable to medical image coding. Rather, we must rely on effective prediction and prediction error coding. This paper compares seven differential pulse code modulation (DPCM) predictors on the basis of average prediction error and channel induced error propagation. A Laplacian model of prediction error distribution suggests a simple family of variable length codes and an algorithm for adaptively selecting that code which best suits the anticipated predictor performance.