MATLAB Implementation of DPCM Encoding Algorithm

The article discusses DPCM encoding, which represents a classical predictive coding methodology. This technique operates by predicting the current sample value based on previous samples and subsequently encoding only the prediction error. The core algorithm involves calculating the difference between actual and predicted values, then quantizing and encoding this differential signal. In MATLAB implementation, this typically involves using shift registers for previous sample storage and difference calculators for error computation. DPCM encoding achieves significant data compression by eliminating statistical redundancies, effectively reducing the required transmission bandwidth. This method finds extensive applications in audio compression (like ADPCM) and image compression standards, where it helps minimize storage requirements and transmission costs while maintaining acceptable information fidelity. The MATLAB code implementation would commonly include functions for linear prediction, error quantization, and encoding table management. Through DPCM encoding, substantial data size reduction can be accomplished with minimal information loss, resulting in optimized storage utilization and bandwidth efficiency. Key MATLAB functions for implementation might include diff() for difference calculation, quantiz() for quantization, and various entropy coding techniques for final compression.