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19 January 2009A comparison study of image spatial entropy
Shannon entropy as a measure of image information is extensively used in image processing applications. This measure
requires estimating a high-dimensional image probability density function which poses a limitation from a practical
standpoint. A number of approaches have been introduced in the literature for estimating image spatial entropy based on
the assumption of Markovianity or homogeneity. This paper provides an overview of these existing approaches and their
differences with Shannon entropy. These definitions are compared by applying them to synthesized test images. These
images are designed in such a way that the spatial arrangements of pixels are changed without altering the histogram,
thus allowing the emphasis to be placed on evaluating image spatial entropy. Furthermore, the computational complexity
aspect of the definitions are discussed. The comparison results show that although the definition of image spatial entropy
based on Aura Matrix provides the most effective outcome among the existing definitions, there are still deficiencies
associated with this definition.
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Q. R. Razlighi, N. Kehtarnavaz, "A comparison study of image spatial entropy," Proc. SPIE 7257, Visual Communications and Image Processing 2009, 72571X (19 January 2009); https://doi.org/10.1117/12.814439