Digital Color Imaging

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

Neural Networks for Transformation to Spectral Spaces

This work is concerned with mapping between the CMYK colour space and spectral space using Artificial Neural Networks (ANNs). The dimensionality of the spectral space is high (typically 31) leading to a large number of weights (or free parameters) in the network. This paper explores the hypothesis that a computational advantage can be obtained, in these cases, by treating the reflectance at each wavelength as being independent of the reflectance at any other wavelength; the implication of this hypothesis is that instead of using a single large ANN, it is possible to use, for example, 31 separate networks, each of which maps to one dimension of the 31-d spectral space. The results showed that as the number of training samples is reduced the advantage of the population of single-wavelength networks over the standard neural network approach increased

Fast Color Space Transformations Using Minimax Approximations

Color space transformations are frequently used in image processing, graphics, and visualization applications. In many cases, these transformations are complex nonlinear functions, which prohibits their use in time-critical applications. In this paper, we present a new approach called Minimax Approximations for Color-space Transformations (MACT).We demonstrate MACT on three commonly used color space transformations. Extensive experiments on a large and diverse image set and comparisons with well-known multidimensional lookup table interpolation methods show that MACT achieves an excellent balance among four criteria: ease of implementation, memory usage, accuracy, and computational speed

The development of the toner density sensor for closed-loop feedback laser printer calibration

A new infrared (IR) sensor was developed for application in closed-loop feedback printer calibration as it relates to monochrome (black toner only) laser printers. The toner density IR sensor (TDS) was introduced in the early 1980’s; however, due to cost and limitation of technologies at the time, implementation was not accomplished until within the past decade. Existing IR sensor designs do not discuss/address: • EMI (electromagnetic interference) effects on the sensor due to EP (electrophotography) components • Design considerations for environmental conditions • Sensor response time as it affects printer process speed The toner density sensor (TDS) implemented in the Lexmark E series printer reduces these problems and eliminates the use of the current traditional “open-loop” (meaning feedback are parameters not directly affecting print darkness such as page count, toner level, etc.) calibration process where print darkness is adjusted using previously calculated and stored EP process parameters. The historical process does not have the ability to capture cartridge component variation and environmental changes which affect print darkness variation. The TDS captures real time data which is used to calculate EP process parameters for the adjustment of print darkness; as a result, greatly reducing variations uncontrolled by historical printer calibration. Specifically, the first and primary purpose of this research is to reduce print darkness variation using the TDS. The second goal is to mitigate the TDS EMI implementation issue for reliable data accuracy

Colorimetric characterization of scanner by measures of perceptual color error

Author name used in this publication: John H. Xin2006-2007 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe

A New framework for an electrophotographic printer model

Digital halftoning is a printing technology that creates the illusion of continuous tone images for printing devices such as electrophotographic printers that can only produce a limited number of tone levels. Digital halftoning works because the human visual system has limited spatial resolution which blurs the printed dots of the halftone image, creating the gray sensation of a continuous tone image. Because the printing process is imperfect it introduces distortions to the halftone image. The quality of the printed image depends, among other factors, on the complex interactions between the halftone image, the printer characteristics, the colorant, and the printing substrate. Printer models are used to assist in the development of new types of halftone algorithms that are designed to withstand the effects of printer distortions. For example, model-based halftone algorithms optimize the halftone image through an iterative process that integrates a printer model within the algorithm. The two main goals of a printer model are to provide accurate estimates of the tone and of the spatial characteristics of the printed halftone pattern. Various classes of printer models, from simple tone calibrations, to complex mechanistic models, have been reported in the literature. Existing models have one or more of the following limiting factors: they only predict tone reproduction, they depend on the halftone pattern, they require complex calibrations or complex calculations, they are printer specific, they reproduce unrealistic dot structures, and they are unable to adapt responses to new data. The two research objectives of this dissertation are (1) to introduce a new framework for printer modeling and (2) to demonstrate the feasibility of such a framework in building an electrophotographic printer model. The proposed framework introduces the concept of modeling a printer as a texture transformation machine. The basic premise is that modeling the texture differences between the output printed images and the input images encompasses all printing distortions. The feasibility of the framework was tested with a case study modeling a monotone electrophotographic printer. The printer model was implemented as a bank of feed-forward neural networks, each one specialized in modeling a group of textural features of the printed halftone pattern. The textural features were obtained using a parametric representation of texture developed from a multiresolution decomposition proposed by other researchers. The textural properties of halftone patterns were analyzed and the key texture parameters to be modeled by the bank were identified. Guidelines for the multiresolution texture decomposition and the model operational parameters and operational limits were established. A method for the selection of training sets based on the morphological properties of the halftone patterns was also developed. The model is fast and has the capability to continue to learn with additional training. The model can be easily implemented because it only requires a calibrated scanner. The model was tested with halftone patterns representing a range of spatial characteristics found in halftoning. Results show that the model provides accurate predictions for the tone and the spatial characteristics when modeling halftone patterns individually and it provides close approximations when modeling multiple halftone patterns simultaneously. The success of the model justifies continued research of this new printer model framework

Spectral characterization of a color scanner by adaptive estimation

Author name used in this publication: John H. xin2004-2005 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe

COLOR MANAGEMENT IMPLEMENTATION IN DIGITAL PHOTOGRAPHY

Digital cameras on the market today have a great potential to become the powerful tool for capturing images for use in all demanding fields (such as artwork digitalization), so many professionals started using digital technology. But, it is often the case, that it is necessary to spend a lot of time for visual editing and making color corrections in various software applications. In this research, some ICC color management techniques were used and tested to investigate the quicker ways to achieve digital images with improved color reproduction accuracy, without visual editing. A testing procedure for characterizing digital camera is described. This procedure is target-based, thus providing objective measurement of quality. The special color reference target for digital camera characterization was developed, applied and tested. The results show that using proposed methodology, the workflow efficiency and color accuracy can be improved