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Spectral Characterization using Continuous Functions

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Spectral characterization is often performed based on the set of measured spectral color signals and corresponding scalar sensor responses. Most methods attempt to reconstruct the sensor sensitivities at a discrete set of specific wavelengths or as a linear combination of basis functions. This paper describes a general method for estimating spectra using a direct regression of the discrete data with a continuous function by means of nonlinear optimization of its parameters. A priori information such as positivity and smoothness constraints and other assumed physical properties of the sensor are incorporated in the estimation process by an appropriate choice of the function. Results are provided for a simple neural network approximator which can be used for modeling of a wide variety of spectral functions. The proposed method is compared with quadratic programming, pseudoinverse, principal eigenvectors, and direct physical measurements.
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Document Type: Research Article

Publication date: January 1, 2004

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  • CIC is the premier annual technical gathering for scientists, technologists, and engineers working in the areas of color science and systems, and their application to color imaging. Participants represent disciplines ranging from psychophysics, optical physics, image processing, color science to graphic arts, systems engineering, and hardware and software development. While a broad mix of professional interests is the hallmark of these conferences, the focus is color. CICs traditionally offer two days of short courses followed by three days of technical sessions that include three keynotes, an evening lecture, a vibrant interactive (poster) papers session, and workshops. An endearing symbol of the meeting is the Cactus Award, given each year to the author(s) of the best interactive paper; there are also Best Paper and Best Student Paper awards.

    Please note: for Purposes of its Digital Library content, IS&T defines Open Access as papers that will be downloadable in their entirety for free in perpetuity. Copyright restrictions on papers vary; see individual paper for details.

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