Publication | Closed Access
Color2Gray
39
Citations
9
References
2005
Year
Unknown Venue
Color ImageImage AnalysisMachine VisionEngineeringColor ReproductionPattern RecognitionImportant Image FeaturesColor2gray AlgorithmColor CorrectionComputer ScienceImage EnhancementImage Quality AssessmentColorizationComputer Vision
Visually important image features often disappear when color images are converted to grayscale. The algorithm introduced here reduces such losses by attempting to preserve the salient features of the color image. The Color2Gray algorithm is a 3-step process: 1) convert RGB inputs to a perceptually uniform CIE L*a*b* color space, 2) use chrominance and luminance differences to create grayscale target differences between nearby image pixels, and 3) solve an optimization problem designed to selectively modulate the grayscale representation as a function of the chroma variation of the source image. The Color2Gray results offer viewers salient information missing from previous grayscale image creation methods.
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