Lossy compression of gray-scale document images by adaptive-offset quantization

This paper describes an adaptive-offset quantization scheme and considers its application to the lossy compression of grayscale document images. The technique involves scalar-quantizing and entropy-coding pixels sequentially, such that the quantizer’s offset is always chosen to minimize the expected number of bits emitted for each pixel, where the expectation is based on the predictive distribution used for entropy coding. To accomplish this, information is fed back from the entropy coder’s statistical modeling unit to the quantizer. This feedback path is absent in traditional compression schemes. Encouraging but preliminary experimental results are presented comparing the technique with JPEG and with fixed-offset quantization on a scanned grayscale text image.