A New ADPCM Image Compression Algorithm and the Effect of Fixed-Pattern Sensor Noise

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Abstract
High speed image compression algorithms that achieve visually lossless quality at low bit-rates are essential elements of many digital imaging systems. In examples such as remote sensing, there is often the additional requirement that the compression hardware be compact and consume minimal power. To meet these requirements a new adaptive differential pulse code modulation (ADPCM) algorithm was developed that significantly reduces edge errors by including quantizers that adapt to the local bias of the differential signal. In addition, to reduce the average bit-rate in certain applications a variable rate version of the algorithm called run adaptive differential coding (RADC) was developed that combines run-length and predictive coding and a variable number of levels in each quantizer to produce bit-rates comparable with adaptive discrete cosine transform (ADCT) at a visually lossless level of image quality. It will also be shown that this algorithm is relatively insensitive to fixed-pattern sensor noise and errors in sensor correction, making it possible to perform pixel correction on the decompressed image.

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