Digital Color Imaging
TL;DR: A survey of color imaging can be found in this article, where the fundamental concepts of color perception and measurement are first presented us-ing vector-space notation and terminology, along with common mathematical models used for representing these devices.
Abstract: This paper surveys current technology and research in the area of digital color imaging. In order to establish the background and lay down terminology, fundamental concepts of color perception and measurement are first presented us-ing vector-space notation and terminology. Present-day color recording and reproduction systems are reviewed along with the common mathematical models used for representing these devices. Algorithms for processing color images for display and communication are surveyed, and a forecast of research trends is attempted. An extensive bibliography is provided.
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TL;DR: This work demonstrates a convenient, versatile approach to dynamically fine-tuning emission in the full colour range from a new class of core-shell upconversion nanocrystals by adjusting the pulse width of infrared laser beams and suggests that the unprecedented colour tunability from these nanocry crystals is governed by a non-steady-state upconverting process.
Abstract: Developing light-harvesting materials with tunable emission colours has always been at the forefront of colour display technologies. The variation in materials composition, phase and structure can provide a useful tool for producing a wide range of emission colours, but controlling the colour gamut in a material with a fixed composition remains a daunting challenge. Here, we demonstrate a convenient, versatile approach to dynamically fine-tuning emission in the full colour range from a new class of core-shell upconversion nanocrystals by adjusting the pulse width of infrared laser beams. Our mechanistic investigations suggest that the unprecedented colour tunability from these nanocrystals is governed by a non-steady-state upconversion process. These findings provide keen insights into controlling energy transfer in out-of-equilibrium optical processes, while offering the possibility for the construction of true three-dimensional, full-colour display systems with high spatial resolution and locally addressable colour gamut.
777 citations
TL;DR: This article presents an overview of existing map processing techniques, bringing together the past and current research efforts in this interdisciplinary field, to characterize the advances that have been made, and to identify future research directions and opportunities.
Abstract: Maps depict natural and human-induced changes on earth at a fine resolution for large areas and over long periods of time. In addition, maps—especially historical maps—are often the only information source about the earth as surveyed using geodetic techniques. In order to preserve these unique documents, increasing numbers of digital map archives have been established, driven by advances in software and hardware technologies. Since the early 1980s, researchers from a variety of disciplines, including computer science and geography, have been working on computational methods for the extraction and recognition of geographic features from archived images of maps (digital map processing). The typical result from map processing is geographic information that can be used in spatial and spatiotemporal analyses in a Geographic Information System environment, which benefits numerous research fields in the spatial, social, environmental, and health sciences. However, map processing literature is spread across a broad range of disciplines in which maps are included as a special type of image. This article presents an overview of existing map processing techniques, with the goal of bringing together the past and current research efforts in this interdisciplinary field, to characterize the advances that have been made, and to identify future research directions and opportunities.
674 citations
TL;DR: The proposed demosaicing algorithm estimates missing pixels by interpolating in the direction with fewer color artifacts, and the aliasing problem is addressed by applying filterbank techniques to 2-D directional interpolation.
Abstract: A cost-effective digital camera uses a single-image sensor, applying alternating patterns of red, green, and blue color filters to each pixel location. A way to reconstruct a full three-color representation of color images by estimating the missing pixel components in each color plane is called a demosaicing algorithm. This paper presents three inherent problems often associated with demosaicing algorithms that incorporate two-dimensional (2-D) directional interpolation: misguidance color artifacts, interpolation color artifacts, and aliasing. The level of misguidance color artifacts present in two images can be compared using metric neighborhood modeling. The proposed demosaicing algorithm estimates missing pixels by interpolating in the direction with fewer color artifacts. The aliasing problem is addressed by applying filterbank techniques to 2-D directional interpolation. The interpolation artifacts are reduced using a nonlinear iterative procedure. Experimental results using digital images confirm the effectiveness of this approach.
462 citations
TL;DR: An overview of the image processing pipeline is presented, first from a signal processing perspective and later from an implementation perspective, along with the tradeoffs involved.
Abstract: Digital still color cameras (DSCs) have gained significant popularity in recent years, with projected sales in the order of 44 million units by the year 2005. Such an explosive demand calls for an understanding of the processing involved and the implementation issues, bearing in mind the otherwise difficult problems these cameras solve. This article presents an overview of the image processing pipeline, first from a signal processing perspective and later from an implementation perspective, along with the tradeoffs involved.
368 citations
TL;DR: The proposed fully automated vector technique can be easily implemented in either hardware or software; and incorporated in any existing microarray image analysis and gene expression tool.
Abstract: Vector processing operations use essential spectral and spatial information to remove noise and localize microarray spots. The proposed fully automated vector technique can be easily implemented in either hardware or software; and incorporated in any existing microarray image analysis and gene expression tool.
348 citations
References
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TL;DR: In this paper, the design, development, and performance of the digital micromirror device (DMD), a spatial light modulator for projection displays, are examined, which is a chip about 2.3 cm/sup 2/covered by 442368 movable mirrors, each 16 mu m on a side.
Abstract: The design, development, and performance of the digital micromirror device (DMD), a spatial light modulator for projection displays, are examined. The DMD covers each memory cell of a CMOS static RAM with a movable micromirror. Electrostatic forces contingent on the data in the cell tilt the mirror either on or off, modulating the light incident on its surface. Light reflected from any on-mirrors passes through a projection lens and creates images on a large screen. Light from the remaining off-mirrors is reflected away from the projection lens and trapped. The standard-resolution version of the DMD corresponds to the National Television System Committee (NTSC) or Phase Alternation Line (PAL) standard. It is a chip about 2.3 cm/sup 2/ covered by 442368 movable mirrors, each 16 mu m on a side. >
134 citations
TL;DR: The algorithm requires extra information, over and above the usual three values mapping human cone responses, from the optical system, and with this additional information, a sampling across the visible range of the reflected, color-signal spectrum impinging on the optical sensor, the authors are able to separate the illumination spectrum from the surface reflectance spectrum.
Abstract: A separation algorithm for achieving color constancy and theorems concerning its accuracy are presented. The algorithm requires extra information, over and above the usual three values mapping human cone responses, from the optical system. However, with this additional information-specifically, a sampling across the visible range of the reflected, color-signal spectrum impinging on the optical sensor-the authors are able to separate the illumination spectrum from the surface reflectance spectrum contained in the color-signal spectrum which is, of course, the product of these two spectra. At the heart of the separation algorithm is a general statistical method for finding the best illumination and reflectance spectra, within a space represented by finite-dimensional linear models of statistically typical spectra, whose product closely corresponds to the spectrum of the actual color signal. Using this method, the authors are able to increase the dimensionality of the finite-dimensional linear model for surfaces to a realistic value. One method of generating the spectral samples required for the separation algorithm is to use the chromatic aberration effects of a lens. An example of this is given. The accuracy achieved in a large range of tests is detailed, and it is shown that agreement with actual surface reflectance is excellent. >
132 citations
TL;DR: The transform-coding concept has been applied to the coding of color images represented by three primary color planes of data and it is shown that, by transform coding, the chrominance content of a color image can be coded with an average of 1.0 bits per element or less without serious degradation.
Abstract: During the past few years several monochromeimage transform-coding systems have been developed. In these systems, a quantized and coded version of a spatial unitary transform of an image is transmitted over a channel, rather than an image itself. In this paper the transform-coding concept has been applied to the coding of color images represented by three primary color planes of data. The principles of spatial transform coding are reviewed and the merits of various methods of color-image representation are discussed. A performance analysis is presented for the color-image transform-coding system. Results of a computer simulation of the coding system are also given. It is shown that, by transform coding, the chrominance content of a color image can be coded with an average of 1.0 bits per element or less without serious degradation. If luminance coding is also employed, the average rate reduces to about 2.0 bits per element or less.
131 citations
TL;DR: The results from training sets indicate that the neural net outperforms the polynomial approximation, and the generalizations, using the trained neural net to predict relationships it has not been trained with, are sometimes rather poor.
Abstract: In the context of colorimetric matching, the intent of color scanner and printer calibrations is to characterize the devicedependent responses to the device-independent representations such as CIEXYZ or CIE 1976 L*a*b* (CIELAB). Usually, this is accomplished by a two-step process of gray balancing and a matrix transformation, using a transfer matrix obtained from multiple polynomial regression. Color calibrations, printer calibrations in particular,
are highly nonlinear. Thus, a new technique, the neural network with the Cascade Correlation learning architecture, is employed for representing the map of device values to CIE standards. Neural networks are known for their capabilities to learn highly nonlinear
relationships from presented examples. Excellent results are obtamed using this particular neural net; in most training sets, the average color differences are about one Eab. This approach is compared to the polynomial approximations ranging from a 3-term
linear fit to a 14-term cubic equation. The results from training sets indicate that the neural net outperforms the polynomial approximation. However, the comparison is not made in the same ground
and the generalizations, using the trained neural net to predict relationships it has not been trained with, are sometimes rather poor. Nevertheless, the neural network is a very promising tool for use in
color calibrations and other color technologies in general.
129 citations
TL;DR: The conversion of a device-independent representation to popular device spaces by means of trilinear interpolation requires substantially fewer lookup table entries with CCIR 601-2 YCbCr and CIELAB.
Abstract: Important standards for device-independent color allow many different color encodings. This freedom obliges users of these standards to choose the color space in which to represent their data. A device-independent interchange color space must exhibit an exact mapping to a colorimetric color representation, ability to encode all visible colors, compact representation for given accuracy, and low computational cost for transforms to and from device-dependent spaces. The performance of CIE 1931 XYZ, CIELUV, CIELAB, YES, CCIR 601-2 YCbCr, and SMPTE-C RGB is measured against these requirements. With extensions, all of these spaces can meet the first two requirements. Quantizing error dominates the representational errors of the tested color spaces. Spaces that offer low quantization error also have low gain for image noise. All linear spaces are less compact than nonlinear alternatives. The choice of nonlinearity is not critical; a wide range of gammas yields acceptable results. The choice of primaries for RGB representations is not critical, except that high-chroma primaries should be avoided. Quantizing the components of the candidate spaces with varying precision yields only small improvements. Compatibility with common image data compression techniques leads to the requirement for low luminance contamination, a property that compromises several otherwise acceptable spaces. The conversion of a device-independent representation to popular device spaces by means of trilinear interpolation requires substantially fewer lookup table entries with CCIR 601-2 YCbCr and CIELAB.
127 citations