Publication | Closed Access
Bi-histogram equalization with a plateau limit for digital image enhancement
288
Citations
25
References
2009
Year
EngineeringColor CorrectionImage MosaicingPlateau LevelDeblurringImage AnalysisHistogram Equalization MethodsComputational ImagingRadiologyHealth SciencesMedical ImagingBi-histogram EqualizationComputer EngineeringSpatial FilteringImage EnhancementImage Quality AssessmentSignal ProcessingComputer VisionMany Histogram EqualizationImage ProcessorImage Restoration
Many histogram equalization based methods have been introduced for the use in consumer electronics in recent years. Yet, many of these methods are relatively complicated to be implemented, and mostly require a high computational time. Furthermore, some of the methods require several predefined parameters from the user, which make the optimal results cannot be obtained automatically. Therefore, this paper presents Bi-Histogram Equalization with a Plateau Level (BHEPL) as one of the options for the system that requires a short processing time image enhancement. First, BHEPL divides the input histogram into two independent sub-histograms. This is done in order to maintain the mean brightness. Then, these sub-histograms are clipped based on the calculated plateau value. By doing this, excessive enhancement can be avoided. Experimental results show that this method only requires 34.20ms, in average, to process images of size 3648x2736 pixels (i.e. 10 Mega pixels images). The proposed method also gives better enhancement results as compared with some multi-sections mean brightness preserving histogram equalization methods <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sup> .
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