Networks for image acquisition, processing and display

The human visual system comprises layers of networks which sample, process, and code images. Understanding these networks is a valuable means of understanding human vision and of designing autonomous vision systems based on network processing. Ames Research Center has an ongoing program to develop computational models of such networks. The models predict human performance in detection of targets and in discrimination of displayed information. In addition, the models are artificial vision systems sharing properties with biological vision that has been tuned by evolution for high performance. Properties include variable density sampling, noise immunity, multi-resolution coding, and fault-tolerance. The research stresses analysis of noise in visual networks, including sampling, photon, and processing unit noises. Specific accomplishments include: models of sampling array growth with variable density and irregularity comparable to that of the retinal cone mosaic; noise models of networks with signal-dependent and independent noise; models of network connection development for preserving spatial registration and interpolation; multi-resolution encoding models based on hexagonal arrays (HOP transform); and mathematical procedures for simplifying analysis of large networks

Predicting the readability of transparent text

Will a simple global masking model based on image detection be successful at predicting the readability of transparent text? Text readability was measured for two types of transparent text: additive (as occurs in head-up displays) and multiplicative (which occurs in see-through liquid crystal display virtual reality displays). Text contrast and background texture were manipulated. Data from two previous experiments were also included (one using very low contrasts on plain backgrounds, and the other using higher-contrast opaque text on both plain and textured backgrounds). All variables influenced readability in at least an interactive manner. When there were background textures, the global masking index (that combines text contrast and background root mean square contrast) was a good predictor of search times (r = 0.89). When the masking was adjusted to include the text pixels as well as the background pixels in computations of mean luminance and contrast variability, predictability improved further (r = 0.91)

A look at motion in the frequency domain

A moving image can be specified by a contrast distribution, c(x,y,t), over the dimensions of space x,y, and time t. Alternatively, it can be specified by the distribution C(u,v,w) over spatial frequency u,v and temporal frequency w. The frequency representation of a moving image is shown to have a characteristic form. This permits two useful observations. The first is that the apparent smoothness of time-sampled moving images (apparent motion) can be explained by the filtering action of the human visual system. This leads to the following formula for the required update rate for time-sampled displays. W(c)=W(l)+ru(l) where w(c) is the required update rate in Hz, W(l) is the limit of human temporal resolution in Hz, r is the velocity of the moving image in degrees/sec, and u(l) is the limit of human spatial resolution in cycles/deg. The second observation is that it is possible to construct a linear sensor that responds to images moving in a particular direction. The sensor is derived and its properties are discussed

An orthogonal oriented quadrature hexagonal image pyramid

An image pyramid has been developed with basis functions that are orthogonal, self-similar, and localized in space, spatial frequency, orientation, and phase. The pyramid operates on a hexagonal sample lattice. The set of seven basis functions consist of three even high-pass kernels, three odd high-pass kernels, and one low-pass kernel. The three even kernels are identified when rotated by 60 or 120 deg, and likewise for the odd. The seven basis functions occupy a point and a hexagon of six nearest neighbors on a hexagonal sample lattice. At the lowest level of the pyramid, the input lattice is the image sample lattice. At each higher level, the input lattice is provided by the low-pass coefficients computed at the previous level. At each level, the output is subsampled in such a way as to yield a new hexagonal lattice with a spacing sq rt 7 larger than the previous level, so that the number of coefficients is reduced by a factor of 7 at each level. The relationship between this image code and the processing architecture of the primate visual cortex is discussed

Uniform apparent contrast noise: A picture of the noise of the visual contrast detection system

A picture which is a sample of random contrast noise is generated. The noise amplitude spectrum in each region of the picture is inversely proportional to spatial frequency contrast sensitivity for that region, assuming the observer fixates the center of the picture and is the appropriate distance from it. In this case, the picture appears to have approximately the same contrast everywhere. To the extent that contrast detection thresholds are determined by visual system noise, this picture can be regarded as a picture of the noise of that system. There is evidence that, at different eccentricities, contrast sensitivity functions differ only by a magnification factor. The picture was generated by filtering a sample of white noise with a filter whose frequency response is inversely proportional to foveal contrast sensitivity. It was then stretched by a space-varying magnification function. The picture summmarizes a noise linear model of detection and discrimination of contrast signals by referring the model noise to the input picture domain

Fourier Decomposition of RR Lyrae light curves and the SX Phe population in the central region of NGC 3201

CCD time-series observations of the central region of the globular cluster NGC~3201 were obtained with the aim of performing the Fourier decomposition of the light curves of the RR~Lyrae stars present in that field. This procedure gave the mean values, for the metallicity, of [Fe/H]$_{ZW}=-1.483 \pm 0.006$ (statistical) $\pm 0.090$ (systematical), and for the distance, $5.000 \pm 0.001$~kpc (statistical) $\pm 0.220$ (systematical). The values found from two RRc stars are consistent with those derived previously. The differential reddening of the cluster was investigated and individual reddenings for the RR Lyrae stars were estimated from their $V-I$ curves. We found an average value of $E(B-V)= 0.23 \pm 0.02$. An investigation of the light curves of stars in the {\it blue stragglers} region led to the discovery of three new SX~Phe stars. The period-luminosity relation of the SX~Phe stars was used for an independent determination of the distance to the cluster and of the individual reddenings. We found a distance of 5.0 kpcComment: To appear in Revista Mexicana de Astronom\'ia y Astrof\'isica, Octuber 2014 issue, Vol 50. 17 pages, 10 figure

Comprehension of Counselor Education Course Materials in Online Versus Face-to-Face Courses

American society has become technology oriented, both inside and outside of the classroom. Some research findings suggest that 31% of students had taken at least one online course in 2012 (Miller & Young-Jones 2012). There are many biases, such as cheating and student biases for both online and traditional face-to-face classes. This review of literature intends to determine if online or traditional courses yield higher comprehension in the course material and how counselor education courses should respond to this research. Research has shown that skillsbased courses should be taught in the traditional setting while theories and other content courses may have equal comprehension in online courses, if students are given supplemental materials

The window of visibility: A psychological theory of fidelity in time-sampled visual motion displays

Many visual displays, such as movies and television, rely upon sampling in the time domain. The spatiotemporal frequency spectra for some simple moving images are derived and illustrations of how these spectra are altered by sampling in the time domain are provided. A simple model of the human perceiver which predicts the critical sample rate required to render sampled and continuous moving images indistinguishable is constructed. The rate is shown to depend upon the spatial and temporal acuity of the observer, and upon the velocity and spatial frequency content of the image. Several predictions of this model are tested and confirmed. The model is offered as an explanation of many of the phenomena known as apparent motion. Finally, the implications of the model for computer-generated imagery are discussed