An analysis of co-occurrence texture statistics as a function of grey level quantization

In this paper, the effect of grey level quantization on the ability of co-occurrence probability statistics to classify natural textures is studied. Generally, as a function of increasing grey levels, many of the statistics demonstrate a decrease in classification ability while a few maintain constant classification accuracy. None of the individual statistics show increasing classification accuracy throughout all grey levels. Correlation analysis is used to rationalize a preferred subset of statistics. The preferred statistics set (contrast, correlation, and entropy) is demonstrated to be an improvement over using single statistics or using the entire set of statistics. If the feature space dimension only…