AUGMENTING JPEG2000 WITH WAVELET COEFFICIENT PREDICTION

This paper presents a novel modification to the Discrete Wavelet Transform used in the JPEG2000 standard. The modification utilises a learning-based method to predict the detail coefficients from the approximation coefficients at each level of the transform, allowing for higher compression rates while maintaining most of JPEG2000's appealing features. A coefficient prediction method based on single-image super resolution literature has been implemented and tested to assess the potential of the compression system. We have observed that the accuracy of the prediction is highly dependent on the content of the test image, with certain features being highly predictable and others not predictable at all. In the best performing test images, we see a quality gain of up to 1.5dB or equivalently a reduction in bit-rate of up to 14% over the JPEG2000 standard.