Aperiodic, clustered-dot, halftone patterns have recently become popular for commercial printing of continuous-tone images with laser, electrophotographic presses, because of their inherent stability and resistance to moiré artifacts. Halftone screens designed using the multistage, multipass, clustered direct binary search (MS-MP-CLU-DBS) algorithm can yield halftone patterns with very high visual quality. But the characteristics of these halftone patterns depend on three input parameters for which there are no known formulas to choose their values to yield halftone patterns of a certain quality level and scale. Using machine learning methods, two predictors are developed that take as input these three parameters. One predicts the quality level of the halftone pattern. The other one predicts the scale of the halftone pattern. To provide ground truth information for training these predictors, human subjects viewed a large number of halftone patches generated from MS-MP-CLU-DBS-designed screens and assigned each patch to one of four quality levels. For each patch, the location of the peak in the radially averaged power spectrum (RAPS) is calculated as a measure of the scale or effective line frequency of the pattern. Experimental results demonstrate the accuracy of the two predictors and the effectiveness of screen design procedures based on these predictors to generate both monochrome and color high quality halftone images.

Digital halftoning is an essential part of the process for printing color, continuous-tone content. Traditionally, the highest quality has been achieved with analog, offset lithographic presses, using color screen sets that yield periodic, clustered-dot halftone patterns. Increasingly, these systems are being supplanted by digital presses that are based on either electrophotographic or inkjet marking processes. Due to the inherent instability of the electrophotographic marking process, periodic, clustered-dot halftone patterns are also widely used with such presses. However, digital presses have much lower resolution than their analog counterparts. Simply mimicking the traditional screen designs used with commercial, offset presses will result in halftone patterns that are more susceptible to moire due to the interaction between the periodic patterns used to render the different color channels. The moire can be reduced by increasing the frequency of the halftone patterns. But this may make the print appear grainier than its analog counterpart. In this paper, we introduce a principled design procedure that allows one to design color screen sets that generate periodic, clustered-dot halftone patterns that improve color stability without increasing graininess.

Digital halftoning is an essential part of the process for printing color, continuous-tone content. Traditionally, the highest quality has been achieved with analog, offset lithographic presses, using color screen sets that yield periodic, clustereddot halftone patterns. Increasingly, these systems are being supplanted by digital presses that are based on either electrophotographic or inkjet marking processes. Due to the inherent instability of the electrophotographic marking process, periodic, clustered-dot halftone patterns are also widely used with such presses. However, digital presses have much lower resolution than their analog counterparts. Simply mimicking the traditional screen designs used with commercial, offset presses will result in halftone patterns that are more susceptible to moire due to the interaction between the periodic patterns used to render the different color channels. This causes instability in the printed colors. The moire can be reduced by increasing the frequency of the halftone patterns. But this may make the print appear grainier than its analog counterpart. In this paper, we introduce a principled design procedure that allows one to design color screen sets that generate periodic, clustered-dot halftone patterns that improve color stability without increasing graininess. We present experimental results to support the benefits of our new color screen set design framework.

Recently, there has been a substantial increase in efforts to develop 3-D visualization technologies that can provide the viewers with a realistic 3-D visual experience. Various terms such as “reality communication” have been used to categorize these efforts. In order to provide the viewers with a complete and realistic visual sensation, the display or visualization system and the displayed content need to match the physiological 3-D information sensing capabilities of the human visual system which can be quite complex. These may include spatial and temporal resolutions, depth perception, dynamic range, spectral contents, nonlinear effects, and vergence accommodation effects. In this paper, first we present an overview of some of the 3-D display research efforts which have been extensively pursued in Asia, Europe, and North America among other areas. Based on the limitations and comfort-based requirements of the human visual system when viewing a nonnatural visual input from 3-D displays, we present an analytical framework that combines main perception and human visual requirements with analytical tools and principles used in related disciplines such as optics, computer graphics, computational imaging, and signal processing. Building on the widely used notion of light fields, we define a notion of perceivable light fields to account for the human visual system physiological requirements, and propagate it back to the display device to determine the display device specifications. This helps us clarify the fundamental and practical requirements of the 3-D display devices for reality viewing communication. In view of the proposed analytical framework, we overview various methods that can be applied to overcome the extensive information needed to be displayed in order to meet the requirements imposed by the human visual system.

Subjective evaluation by human observers is usually used to analyze and select an edge detector parametric setup when real-world images are considered. We propose a statistical objective performance analysis and detector parameter selection, using detection results produced by different detector parameters. Using the correspondence between the different detection results, an estimated best edge map, utilized as an estimated ground truth (EGT), is obtained. This is done using both a receiver operating characteristics (ROC) analysis and a Chi-square test, and considers the trade off between information and noisiness in the detection results. The best edge detector parameter set (PS) is then selected by the same statistical approach, using the EGT. Results are demonstrated for several edge detection techniques, and compared to published subjective evaluation results. The method developed here suggests a general tool to assist in practical implementations of parametric edge detectors where an automatic process is required.

A method of calculating numerically the optical transfer function appropriate to any type of image motion and vibration, including random ones, has been developed. This method has been verified experimentally, and the close agreement justifies implementation in image restoration for blurring deriving from any type of image motion. The goal of this research is to recover the original image from its degraded version. There are many methods of image restoration based on the point spread function. One of the common methods is the Wiener filter. Here, some image restorations of physically degraded images are presented, based on a constrained least squares improvement of the original Wiener filter. The key to restoration is determination of the optical transfer function unique to each particular image motion and vibration.