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Rhromatic 9nduction and Rontrast Basking) similar models- different goals[ Sandra ñiménez- Xavier Otazu- Valero Daparra and ñesús Balo 1. INTRODUCTION: 3. EXPERIMENTS: 4. RESULTS: 5. DISCUSSION: 6. REFERENCES: Docal interaction between sensors tuned to a particular feature at certain spatial position and neighbor sensors explains a wide range of psychophysical factsè Basking of Spatial Patterns The particular 9nduction and Basking models considered here have the same linear+nonlinear scheme) - Efficient coding skeptics: The organization of mechanisms responsible for induction is not guided by redundancy reduction principleè - Efficient coding lovers: The models differ mainly in the values of their parameters- so one could think that the same spatioUchromatic sensors change depending on the environment to attain the same efficency goalè Universitat de València- SpainA RVR- SpainA 2. OUR WORK: ¿ = ? &ormal and qualitative similarities Same statistical goal q-1-2 3-4-5 q-1 4-5 U 0mpirically assess the reduction in mutual information ) .qP “fter the wavelet transform .1P “fter the nonUlinear interaction stage U Stimulus) 9nduction 9mages Hatural 9mages 5-6 1 E [q] Otazu- Xè- Vanrell- Bè- and Parraga- “è- “Butiresolution wavelet framework models brigthness induction effects-” Vision Research 3E.4P- 622–64q .1FFEPè [1] Otazu- Xè- Parraga- “è- and Vanrell- Bè- “Toward a unified chromatic induction model-” ñournal of Vision qF.q1P .1FqFPè [2] Bonnier- Pè- x Shevell- Sè íè .1FF2Pè “Darge shifts in color appearance from patterned chromatic backgrounds”è Hature Heuroscience- 5- EFq–EF1è [3] Watson- “è and Solomon- ñè- ““ model of visual contrast gain control and pattern masking-” ñOS“ “ q3- 126(–12(q .q((6Pè [4] Daparra- Vè- Buñoz Barí- ñè- and Balo- ñè- “–ivisive normalization image quality metric revisited-” ñOS“ “ 16.3P- E41–E53 .1FqFPè [5] Balo- ñè and Daparra- Vè- “Psychophysically tuned divisive normalization approximately factorizes the P–& of natural images-” Heural Romputation 11.q1P- 2q6(–21F5 .1FqFPè [6] ”ethge- Bè- “&actorial coding of natural images) how effective are linear models in removing higherUorder dependencies[-” ñournal of the Optical Society of “merica “ 12.5P- q142–q15E .1FF5Pè [E] Parraga- Rè- Vazquez- ñè- and Vanrell- Bè- ““ new cone activationUbased natural image dataset-” Perception .SupplèP 25- qEF .1FF(Pè [(] Warrar- Bè- Viénot- &è- “Regulation of chromatic induction by neighboring images”è ñè Optè Socè “m “è- 11) 1q(6U11F5 .1FF4Pè ”rightness and Rhromatic 9nduction purple lime b a a a a b Results from [(]
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