A perceptually based adaptive sampling algorithm

Abstract

A perceptually based approach for selecting image samples has been developed. An existing image processing vision model has been extended to handle color and has been simplified to run efficiently. The resulting new image quality model was inserted into an image synthesis program by first modifying the rendering algorithm so that it computed a wavelet representation. In addition to allowing image quality to be determined as the image was generated, the wavelet representation made it possible to use statistical information about the spatial frequency distribution of natural images to estimate values where samples were yet to be taken. Tests on the image synthesis algorithm showed that it correctly handled achromatic and chromatic spatial detail and that it was able predict and compensate for masking effects. The program was also shown to produce images of equivalent visual quality while using different rendering techniques.