Least-squares image estimation on a multiresolution pyramid

A class of linear recursive image estimation methods, based on multiresolution image representations, is introduced. Although recursive, the estimators are causal not in the image plane but in a third dimension, that of the scale index. The estimators are efficient computationally and are in general suboptimal for a class of image models based explicitly on the scale-space underlying the multiresolution description. Methods are also presented for adapting the estimates to local image structure across a wide range of scales. The estimates are robust and outperform many of the techniques reported in the literature in terms of computational efficiency, signal-to-noise gain, and subjective appearance. A brief presentation of the theoretical basis of the methods is followed by experimental results and conclusions on the potential of the approach