The recently patented stochastic matrix method of function recovery offers workable alternatives to traditional methods of image analysis. This paper illustrates its application to image compression and its application to image enhancement (image zoom). In the former application, it appears to be competitive with JPEG DCT with respect to file size but with the added advantage that it does not suffer from artifacts of that coder. In the latter application, it appears to be clearly superior to the bi-cubic interpolation that is used by popular commercial graphics packages. An important and characteristic property of the stochastic matrix method (SMM) of function recovery is its free parameter sigma that can be optimized, e.g. by an intelligent system, to change the nature of the image analysis.
['Daniel Howard', 'Joseph Kolibal']
Image Analysis by Means of the Stochastic Matrix Method of Function Recovery