Burst error recovery for VF arithmetic coding

One of the disadvantages of compressed data is their vulnerability, that is , even a single corrupted bit ill compressed data may destroy the decompres sed data completely. Therefore, Variable-to-fixed length Arithmetic Coding, or VFAC, with error detecting capability is discussed. However, implementa ble error recovery method fur compressed data has never been proposed. This paper proposes Burst Error Recovery Variable-to-Fixed length Arithmetic Co ding, or BERVFAC as well as Error Detecting Variable-to-Fixed length Arithm etic Coding, or EDVFAC. Both VFAC schemes achieve VF coding by inserting th e internal states of the decompressor into compressed data. The internal st ates consist of width and offset of the subinterval corresponding to the de compressed symbol and are also used for error detection. Convolutional oper ations are applied to encoding and decoding in order to propagate errors an d improve error control capability. The proposed EDVFAC and BERVFAC are eva luated by theoretical analysis and computer simulations. The simulation res ults show that more than 99.99% of errors can be detected by EDVFAC. For BE RVFAC, over 99.95% of l-burst errors can be corrected for l less than or eq ual to 32 and greater than 99.99% of other errors can be detected. The simu lation results also show that the time-overhead necessary to decode the BER VFAC is about 12% when 10% of the received words are erroneous.