Conditional entropy coding of digital pictures

Two new coding schemes for bit-rate reduction of digital images are proposed. Both coding schemes are based on a new model which makes use of the conditional statistical properties of the image signals. These statistics are used to construct codebooks for the encoding and decoding of the digital images. In the first scheme, the code words are assigned in such a way as to provide a signal with long bit runs. Such a signal is then efficiently run-length coded using CCITT codes. In the second scheme, each picture element (PEL) value is coded by variable-length code words according to the values of previously transmitted PELs. The performance of both schemes in terms of entropy and bit-rate are compared with an optimum predictive coder. The simulation results indicate that the proposed schemes have a significant advantage over standard predictive encoders. A method to reduce the storage requirement for the encoder and decoder codebooks is also proposed.