Non-linear filter banks for error-resilient image compression

Linear filter banks and wavelet transforms have been widely researched and have many applications including sub-band image coding. For good performance the filter banks should posses the properties of both critical decimation and perfect reconstruction, which together imply that the sub-band representation is both complete and non-redundant. More recently non-linear filter banks satisfying the constraints of both critical decimation and perfect reconstruction have been proposed. Such filter banks allow the use of median and other non-linear operators, and have been shown to give improved subjective quality for image compression. The use of median operations gives the filters important out-lier rejection properties. This paper examines the use of non-linear filter banks for image compression and transmission over noisy channels. Example filters are designed using median operations and are shown to have an improved resilience to channel errors.