This article and the associated data and programs provided with it are intended to assist color engineers and scientists in correctly implementing the recently developed CIEDE2000 color-difference formula. We indicate several potential implementation errors that are not uncovered in tests performed using the original sample data published with the standard. A supplemental set of data is provided for comprehensive testing of implementations. The test data, Microsoft Excel spreadsheets, and MATLAB scripts for evaluating the CIEDE2000 color difference are made available at the first author's website. Finally, we also point out small mathematical discontinuities in the formula. © 2004 Wiley Periodicals, Inc. Col Res Appl, 30, 21–30, 2005; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/col.20070

The CIEDE2000 color-difference formula: Implementation notes, supplementary test data, and mathematical observations

We present a new algorithm for a robust family of Earth Mover's Distances - EMDs with thresholded ground distances. The algorithm transforms the flow-network of the EMD so that the number of edges is reduced by an order of magnitude. As a result, we compute the EMD by an order of magnitude faster than the original algorithm, which makes it possible to compute the EMD on large histograms and databases. In addition, we show that EMDs with thresholded ground distances have many desirable properties. First, they correspond to the way humans perceive distances. Second, they are robust to outlier noise and quantization effects. Third, they are metrics. Finally, experimental results on image retrieval show that thresholding the ground distance of the EMD improves both accuracy and speed.

/pdf/fast-and-robust-earth-mover-s-distances-fgazceuh5l.pdf

Fast and robust Earth Mover's Distances

We introduce an effective technique to enhance the images captured underwater and degraded due to the medium scattering and absorption. Our method is a single image approach that does not require specialized hardware or knowledge about the underwater conditions or scene structure. It builds on the blending of two images that are directly derived from a color-compensated and white-balanced version of the original degraded image. The two images to fusion, as well as their associated weight maps, are defined to promote the transfer of edges and color contrast to the output image. To avoid that the sharp weight map transitions create artifacts in the low frequency components of the reconstructed image, we also adapt a multiscale fusion strategy. Our extensive qualitative and quantitative evaluation reveals that our enhanced images and videos are characterized by better exposedness of the dark regions, improved global contrast, and edges sharpness. Our validation also proves that our algorithm is reasonably independent of the camera settings, and improves the accuracy of several image processing applications, such as image segmentation and keypoint matching.

/pdf/color-balance-and-fusion-for-underwater-image-enhancement-4cjuexzr3u.pdf

Color Balance and Fusion for Underwater Image Enhancement

A thin-film, white-light-emitting diode device includes a reflective, conductive thin-film structure and a semi-transparent, conductive thin-film structure One or more thin-film layers are formed between the reflective and semi-transparent conductive thin-film structures to form two or more commonly-controlled microcavity structures The thin-film layers emit white light in response to current provided by the conductive thin-film structure Each of the two or more commonly-controlled microcavity structures has a different resonant frequency within one or more optical cavities and emits light with a smaller spectral range than the spectral range of the white-light-emitting thin-film layer(s) A combination of light emitted from the two or more commonly-controlled microcavity structures is white

Oled device having improved light output

An optical reader, which is operable in a “host commands” mode and a “host routines” mode. In the “host commands” mode, the reader receives and executes a script routine module from a host. In the “host routines” mode, the reader receives a script routine Module identifier from the host, and the reader, in turn, executes a selected one of a plurality of reader-stored script routine modules based on the identifier.

Customizable optical reader

A process for the preparation of a toner comprising: preparing an organic phase comprised of a first nonpolar olefinic monomer, a second nonpolar diolefinic monomer, a pigment, a free radical initiator, and optionally a charge control agent; adding the organic phase to an aqueous phase comprised of at least one surfactant; shearing the organic phase into the aqueous phase to form a microdroplet suspension of the organic phase dispersed in the aqueous phase; heating and polymerizing the microdroplets in the suspension to form nonpolar olefinic resin particles; halogenating the nonpolar olefinic resin particle mixture to form a nonpolar toner having a halopolymer resin outer surface or encapsulating shell; and optionally isolating the surface halogenated nonpolar toner.

Toner compositions and processes thereof

A model was developed for the effect of gloss on reflected color, taking the measurement geometry of the color measuring device into account. It considers the total front surface reflectance of a given sample to be independent of gloss and determined only by its refractive index and the angle of the incident beam. Although the total front surface reflectance is fixed, its specular component increases (and the diffuse component decreases) with increasing sample gloss. Therefore, the diffuse reflectance factor measured by a spectrophotometer decreases with sample gloss. In this article, a defined curve was fitted to the measured reflectance factor of black xerographic print samples having a range of gloss values for the 0/45 and diffuse spectrophotometer geometries, and this curve was used to predict the CIELAB color values for samples of the other colors at various gloss levels. The predicted color was compared to the measured color for cyan, magenta, yellow, red, green, and blue images that spanned a wide range of gloss. The RMS color error between the predicted and measured color of all of these images was found to be about 3 CIELAB ΔE* units. © 1999 John Wiley & Sons, Inc. Col Res Appl, 24, 369–376, 1999

The effect of gloss on color

This invention specifically covers one of the many image quality (IQ) metrics that can be part of an overall image quality analysis engine. The specific problem with image quality addressed with this metric is that of a region of a printed (or copied) image, which was intended to have a uniform color, but which shows visible color variations. The color variation can have many different forms, both with respect to the type of color difference and with respect to the spatial nature of the non-uniformities. The image quality analysis system readily distinguishes between non-uniformities in the following different categories, including: (a) amplitude modulated cluster dot halftone patterns; (b) frequency modulated halftone patterns (e.g., stochastic screens); (c) irregular two-dimensional variations from noise; (d) isolated (non-periodic) one-dimensional streaks; (e) periodic, one-dimensional bands; and (f) two-dimensional periodic variations (Moire). The results from the image quality analysis can then be used as a basis for diagnosing machine problems.

Image processing algorithm for characterization of uniformity of printed images

In preparation for rendering respective portions of a document via a respective plurality of engines, objects within the document are identified and characterized. A determination is made as to whether gamut variations between the engines might result in objectionable variations in the appearance of rendered versions of identified objects having similar characteristics. For those objects within the document for which the determination is made that variations might be objectionable, a target gamut is selected to be an intersection gamut of the engines to be used to render the document. For those objects within the document for which the determination is made that variations would be unobjectionable, the target gamut is selected to be that of selected individual engines. A system for selecting target gamuts for objects within a document can include an object identifier, a characteristic identifier and a gamut selector.

Edul N. Dalal

Papers

The CIEDE2000 color-difference formula: Implementation notes, supplementary test data, and mathematical observations

Toner compositions and processes thereof

The effect of gloss on color

Image processing algorithm for characterization of uniformity of printed images

Gamut selection in multi-engine systems