Publication | Closed Access
Local correlations, information redundancy, and sufficient pixel depth in natural images
42
Citations
27
References
2003
Year
EngineeringBrain MappingDepth MapSocial SciencesImage AnalysisPattern RecognitionSufficient Pixel DepthInformation RedundancyJoint Probability DistributionVision RecognitionImage FormationMachine VisionCognitive ScienceNeuroimagingVisual PathwayVisual ProcessingMedical Image ComputingComputer VisionLocal CorrelationsComputational NeuroscienceComputer Stereo VisionNeuroscienceImage ResolutionMutual InformationStereoscopic ProcessingMathematical Framework
A mathematical framework that permits the factorization of a joint probability distribution into its localized components for a two-dimensional array of pixels is presented. The factorization was used to estimate the contribution to mutual information of two- (I2) and three-pixel (I3) luminance correlations for a large ensemble of natural images analyzed at various spatial scales and pixel depths b. It is shown that both I2 and I3 saturate at b approximately 6 bits per pixel. Three-pixel correlations are shown to produce only a marginal increase of information redundancy (4%) over two-pixel correlations (50%). Implications for neural representation in visual cortex are discussed.
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