Cluster dot dithering is one of the most common halftoning techniques. It is fast, low in complexity and allows for variability and inconsistencies in point spreads in printer outputs. Determination of the basic dither cell size is critical for the quality of the halftoning. There is a basic tradeoff between large and small cell sizes: spatial resolution versus gray tone resolution. Large dither cell sizes produce good tone resolution but poorly reproduce spatial details in the image. Small dither cells, on the other hand, produce fine spatial resolution but lack the tone resolution which produces smooth gray tone gradients in halftone images. Typically, cluster dot dithering assumes a predefined dither cell size that compromises between fine detail reproduction and good gray tone reproduction. It is clearly advantageous to allow variability in the dither cell size using small cell sizes in image regions of fine details and using large cell sizes in image regions where gray tones are to be accurately reproduced. In this paper, we introduce and discuss several adaptive dithering techniques based on cluster dot dithering.
A method to halftone an image using a set of dither bitmaps designed to minimize the visibility of halftone patterns is reported. These dither bitmaps for different gray levels are partially correlated with each other with an associated correlation interval. As a result, the halftone patterns for each gray level are more optimal than those associated with the fully correlated dither bitmap techniques, without the introduction of objectionable artifacts that are associated with the fully uncorrelated dither bitmaps approach. Implementation details are given as well as the experimental results.
A colorimetric printer model takes as its input a set of ink values and predicts the resulting printed color, as specified by reflectance or tristimulus values. The Neugebauer model has been widely used to predict the colorimetric response of halftone color printers. In this paper, techniques for optimizing the Neugebauer model are presented and compared. These include optimization of the Yule–Nielsen factor that accounts for light scattering in the paper, estimation of the dot area functions, and extension to a cellular model. A new technique is described for optimizing the Neugebauer primaries using weighted spectral regression. Experimental results are presented for xerographic printers using two halftone screens: the random or rotated dot, and the dot-on-dot screen. Use of the Yule–Nielsen factor, the cellular framework, and spectral regression considerably increase model accuracy.
This paper introduces a velocital information feature that is extracted for each frame of an image sequence. The feature is based on the optical flow in each frame. A mathematical formulation for the velocital information feature is derived. Charting the feature over a sequence provides a quality metric called velocital information content (VIC). The relationship of VIC to the spatial and temporal information content is shown. VIC offers a different role from traditional transmission-based quality metrics which require two images: the original input image and degraded output image to calculate the quality metric. VIC can detect artifacts from a single image sequence by charting variations from the norm. Therefore, VIC offers a metric for judging the quality of the image frames prior to transmission, without a transmission system or without any knowledge of the higher quality image input. The differences between VIC and transmission-oriented quality metrics can provide a different role for VIC in analysis and image sequence processing. Results show that VIC is able to detect gradual and sudden changes in an image sequence. Results are shown for using VIC as a filter on electro-optical infrared image sequences where VIC detects frames suffering from erratic noise.
In this paper, the utilization of morphological pyramids for object tracking is detailed. Image pyramids, constructed via morphological operations and subsampling, have been previously applied to the image compression and progressive transmission problems. We extend the application of the morphological pyramid to the video tracking problem—following the position of a previously identified moving object in a sequence of video frames. Morphological pyramids allow both a considerable tolerance of noise and a saving in computational time for video tracking. Experimental results from the application of the morphological pyramid to noisy IR image sequences are presented. Our results show that the computational efficiency of the morphological pyramid for tracking significantly improves upon the traditional fixed resolution approach by organizing a search from coarse to fine. Furthermore, the morphological pyramid significantly enhances performance over the comparable linear pyramid methods.
In this paper, we formulate a complete approach of line matching, based on geometrical invariants. In the proposed technique, it is not necessary to have a priori knowledge about the observed objects and the camera calibration coefficients. This technique can be used in on-line tasks in robotics, tracking, and target recognition applications. A line segment is locally represented by invariant parameters under the group of displacements within an image and the scale changes. The matching process is achieved through two steps, features clustering and hypotheses verification. In order to be matched, a pair of lines represented by neighboring features in the parameter space must satisfy geometrical constraints (relative angle and distance) in the image plane. Conducted analysis and tests proved the stability of proposed line invariants under complex movements of camera. Experimental results have shown a high rate matching on different types of computer generated and real images.
The edge of the moon is used as a high contrast target to perform a visible ‘‘knife-edge’’ modulation transfer function (MTF) test on a digital imaging system in geostationary orbit. An image of the moon is taken in the camera’s normal scanning mode, and traces across the sharpest edge are used to form an edge spread function (ESF). The ESF is then used to produce a MTF estimate. In a second trial, the imaging system stares as the lunar edge drifts by, creating an edge spread function with a much higher effective spatial sampling rate. In each case, a technique of combining and resampling traces is employed to adapt the knife-edge MTF technique for use with sampled data. The resulting MTF curves track ground test frequencies to within 5%. The phase transfer function is also extracted, and the process is repeated in the north/south direction. The functions are combined to produce a two-dimensional optical transfer function (OTF) which is used as an inverse filter to restore raw images via deconvolution. The approach thus offers a means of testing the MTF and OTF of orbiting image acquisition devices as well as enhancing satellite imagery.
The interchange and printing of digital color images is not as simple as one might naively believe. It is much more than specifying a set of RGB or CMYK code values. Each input and output device will have its own unique color characteristics; therefore the same RGB values will correspond to different colors on different devices.