Frequency estimation for complex field image channel coding

BCH (Bose-Chaudhuri-Hocquenghem) codes over complex fields in the frequency domain have been proposed for image coding applications as robust channel coding methods. The embedded problem of estimation of complex sinusoids cor rupted by white additive noise may be solved in different ways. A standard approach for modelling such signals employs low-order nearly nonstationary autoregressive (AR) models with complex parameters. In the paper linear pre diction/least squares based methods are used for parameter estimation inclu ding forward linear prediction (FLP) and forward-backward linear prediction (FBLP). The two parameter estimation methods have been applied to the firs t- and the second-order AR models with minimal number of samples to obtain efficient frequency estimators for decoding of BCH codes. Computer simulati on has been carried out to compare different frequency estimation algorithm s with regards to three significant criteria: frequency resolution, computi ng complexity and coding redundancy. The results show that different algori thms exhibit optimal combinations of characteristics for different constrai nts and Importance of criteria.