6533b829fe1ef96bd1289796
RESEARCH PRODUCT
The role of perceptual contrast non-linearities in image transform quantization
J. SoretJesús MaloFrancesc J. FerriJosé M. ArtigasJesús V. Albertsubject
Image codingTraining setbusiness.industryQuantization (signal processing)media_common.quotation_subjectComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONPerceptionSignal ProcessingComputer visionComputer Vision and Pattern RecognitionArtificial intelligencePerceptual DistortionMinificationbusinessAlgorithmMathematicsmedia_commondescription
Abstract The conventional quantizer design based on average error minimization over a training set does not guarantee a good subjective behavior on individual images even if perceptual metrics are used. In this work a novel criterion for transform coder design is analyzed in depth. Its aim is to bound the perceptual distortion in each individual quantization according to a non-linear model of early human vision. A common comparison framework is presented to describe the qualitative behavior of the optimal quantizers under the proposed criterion and the conventional rate-distortion based criterion. Several underlying metrics, with and without perceptual non-linearities, are used with both criteria. Analytical results show that the proposed design criterion gives rise to a JPEG-like quantization if a simple linear metric is used. Experimental results show that significant improvements over the perceptually weighted rate-distortion approach are obtained if a more meaningful non-linear metric is used.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2000-02-01 | Image and Vision Computing |