Title :
Image coding by auto regressive synthesis
Author :
Jain, Anil K. ; Ranganath, Surendra
Author_Institution :
University of California, Davis
Abstract :
A new method of image coding by autoregressive (AR) synthesis is presented. The physics of image formation suggests that an image may be considered as a power spectrum. Using this formulation a Cosine transform of the sampled image is shown to yield a set of autocorrelations. These are used to find an equivalent AR model whose parameters are encoded for transmission. Compared to conventional Cosine transform coding, this method is shown to give superior resolution and is shown to suppress the "block-effects" present in block-by-block transform coding methods. Distinction between this method and linear predictive coding (LPC) used for speech data compression is made. Extensions and examples for two dimensional images are given.
Keywords :
Autocorrelation; Distribution functions; Image coding; Image sampling; Linear predictive coding; Signal processing; Signal processing algorithms; Signal synthesis; Speech coding; Transform coding;
Conference_Titel :
Acoustics, Speech, and Signal Processing, IEEE International Conference on ICASSP '80.
DOI :
10.1109/ICASSP.1980.1170876