Efficient and reliable dynamic quality control for compression of compound document images

Compound images contain a mixture of natural images, text, and graphics. They need special care in the use of compression because text and graphics cannot withstand the significant distortion that is acceptable for natural images. One solution is to identify the areas that need to have higher settings in a dynamic quality control scheme, as supported by JPEG-SPIFF and JPEG 2000. We propose a scheme to identify those regions using a discrimination function that works with a non-linear transform to reliably identify edges, and at the same time avoid false positive detection on regions with complex patterns. It does so by exploiting the properties of histograms of coefficients of this block transform, and their entropy function, which we show can be computed efficiently via table look-up. Experimental results demonstrate the performance of the new scheme, compared to other methods in the literature.