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ECE 638: Principles of Digital Color Imaging Systems

This lecture discusses the discrete wavelength trichromatic model for characterizing the human visual subspace. Topics include stimulus, sensor response, projection operators, and the extraction of the fundamental component of a stimulus. The lecture also explores questions about invisible stimuli, physically realizable colors, and the transformation between color matching matrices.

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ECE 638: Principles of Digital Color Imaging Systems

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  1. ECE 638: Principles ofDigital Color Imaging Systems Lecture 10: Discrete Wavelength Models Characterization of Human Visual Subspace

  2. Synopsis • Review of discrete wavelength model

  3. Discrete-wavelength trichomatic model • Stimulus • Sensor response • Response of the i-th channel • Define • Span(S) defines HVS subspace • Stack sensor outputs

  4. Definition of projection operator • Projection operator is a linear operator that extracts the fundamental component of the stimulus , i.e. • Equivalent forms of projection operator

  5. Extraction of fundamental component of stimulus: an imaging systems interpretation • A complete imaging system can be thought of as a capture device followed by a display device. • The process of extracting the fundamental component of the stimulus can be viewed in this way Sensor Display

  6. Questions about the human visual subspace • Question 1: Are there real stimuli that are invisible? • Answer: “No” • Question 2: Are there real stimuli for which ? • Not yet answered • Question 3: What colors in the fundamental space are physically realizable with the addition of a black space component, i.e. what colors have a physically realizable metamer? • Fundamental component must be a non-negative linear combination of the columns of the projector operator

  7. Orthonormal basis for R • It can be shown (see Appendix A of Wolski’s paper) that the projection operator can be expressed as • where is a 31x3 matrix whose columns form an orthonormal basis for the human visual subspace • Thus the fundamental component of any stimulus can be expressed as

  8. Transformation between color matching matrix AXYZ and basis functions F 31x3

  9. Orthonormal basis functions F and a realizable metamer • text Realizable metamer to F F spectral basis set

  10. Columns of R (fundamental components of monochromatic stimuli) in F-space Columns of R in F-space Normalized to unit length Columns of R in F-space Non-normalized Points indicate fundamental component of spectral locus Solid arcs show octant of unit sphere. Dashed line is “purple line”

  11. Elements of fundamental space realizable without a black-space component – start with cone functions Vos and Walraven cone functions in F-space Cone functions reported by Vos and Walraven Since cone functions are non-negative and span human subspace by definition, they are realizable without a black-space component. Points in convex hull of correspond to stimuli realizable with no null-space component

  12. Expansion of set of directly realizable colors by region-growing Spectra corresponding to labeled points on left F-space representation of all realizable colors Colors inside inner dotted region are realizable without a black-space component. Colors outside this region, but inside outer dotted region are realizable only with a black-space component.

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