Gary W. Meyer

A perceptually based adaptive sampling algorithm

A perceptually based approach for selecting image samples has been developed. An existing image processing vision model has been extended to handle color and has been simplified to run efficiently. The resulting new image quality model was inserted into an image synthesis program by first modifying the rendering algorithm so that it computed a wavelet representation. In addition to allowing image quality to be determined as the image was generated, the wavelet representation made it possible to use statistical information about the spatial frequency distribution of natural images to estimate values where samples were yet to be taken. Tests on the image synthesis algorithm showed that it correctly handled achromatic and chromatic spatial detail and that it was able predict and compensate for masking effects. The program was also shown to produce images of equivalent visual quality while using different rendering techniques. CR

An experimental evaluation of computer graphics imagery

Accurate simulation of light propagation within an environment and perceptually based imaging techniques are necessary for the creation of realistic images. A physical experiment that verifies the simulation of reflected light intensities for diffuse environments was conducted. Measurements of radiant energy flux densities are compared with predictions using the radiosity method for those physical environments. By using color science procedures the results of the light model simulation are then transformed to produce a color television image. The final image compares favorably with the original physical model. The experiment indicates that, when the physical model and the simulation were viewed through a view camera, subjects could not distinguish between them. The results and comparison of both test procedures are presented within this paper.

Wavelength dependent reflectance functions

A wavelength based bidirectional reflectance function is developed for use in realistic image synthesis. A geodesic sphere is employed to represent the BRDF, and a novel data structure is used to store this description and to recall it for rendering purposes. A virtual goniospectrophotometer is implemented by using a Monte Carlo ray tracer to cast rays into a surface. An optics model that incorporates phase is used in the ray tracer to simulate interference effects. An adaptive subdivision technique is applied to elaborate the data structure from rays scattered into the hemisphere above the surface. The wavelength based BRDF and virtual goniospectrophotometer are utilized to analyze and make pictures of thin films, idealized pigmented materials, and pearlescent paints.

Wavelength selection for synthetic image generation

Abstract The efficient synthesis of color in computer graphics is dependent on modelling the correct number and spacing of wavelengths across the visible spectrum. It has recently been shown that the opponent representation of the fundamental spectral sensitivity functions is optimal from the point of view of statistical communication theory. This result is used in this paper to guide the selection of wavelengths for synthetic image generation. Gaussian quadrature with the opponent fundamentals as weighting functions is used to choose the wavelengths. This approach is shown to be superior to using Gaussian quadrature with the fundamental spectral sensitivity functions or the CIE XYZ matching functions. The technique is evaluated by using color difference calculations and by comparisons between a real scene and a computer generated picture of that scene.

Color-defective vision and computer graphics displays

A color space defined by the fundamental spectral sensitivity functions of the human visual system is used to assist in the design of computer graphics displays for color-deficient users. The functions are derived in terms of the CIE standard observer color-matching functions. The Farnsworth-Munsell 100-hue test, a widely used color vision test administered using physical color samples, is then implemented on a digitally controlled color television monitor. The flexibility of this computer graphics medium is then used to extend the Farnsworth-Munsell test in a way that improves the specificity of the diagnoses rendered by the test. The issue of how the world appears to color-deficient observers is addressed, and a full-color image is modified to represent a color-defective view of the scene. Specific guidelines are offered for the design of computer graphics displays that will accommodate almost all color-deficient users.<<ETX>>

Perceptual color spaces for computer graphics

Perceptually uniform color spaces can be a useful tool for solving computer graphics color selection problems. However, before they can be used effectively some basic principles of tristimulus colorimetry must be understood and the color reproduction device on which they are to be used must be properly adjusted. The Munsell Book of Color and the Optical Society of America (OSA) Uniform Color Scale are two uniform color spaces which provide a useful way of organizing the colors of a digitally controlled color television monitor. The perceptual uniformity of these color spaces can be used to select color scales to encode the variations of parameters such as temperature or stress.

Modeling pigmented materials for realistic image synthesis

This article discusses and applies the Kubelka-Munk theory of pigment mixing to computer graphics in order to facilitate improved image synthesis. The theories of additive and subtractive color mixing are discussed and are shown to be insufficient for pigmented materials. The Kubelka–Munk theory of pigment mixing is developed and the relevant equations are derived. Pigment mixing experiments are performed and the results are displayed on color television monitors. A paint program that uses Kubelka–Munk theory to mix real pigments is presented. Theories of color matching with pigments are extended to determine reflectances for use in realistic image synthesis.

A frequency based ray tracer

A ray tracer has been developed that synthesizes images directly into the frequency domain. This makes it possible to use a simple vision model to control where rays are cast into a scene and to decide how rays should be spawned once an object is intersected. In this manner the most visible artifacts can be removed first and noise can be channeled into those areas of an image where it is least noticeable. The resulting image is produced in a format that is consistent with many image compression and transmission schemes. CR

Applying appearance standards to light reflection models

Appearance standards for gloss, haze, and goniochromatic color are applied to computer graphic reflection models. Correspondences are derived between both the gloss and haze standards and the specular exponent of the Phong model, the surface roughness of the Ward model, and the surface roughness of the Cook-Torrance model. Metallic and pearlescent colors are rendered using three aspecular measurements defined in a proposed standard for goniochromatic color. The reflection models for gloss and goniochromatic color are combined to synthesize pictures of clear coated automotive paint. Advantages of using appearance standards to select reflection model parameters include the small number of required measurements and the inexpensive commercially available instruments necessary to acquire the data. The use of a standard appearance scale also provides a more intuitive way of selecting the reflection model parameters and a reflection model independent method of specifying appearance.

Comparison of two image quality models

In recent years a number of different vision models have been proposed to assist in the evaluation of image quality. However, there have been few attempts to independently evaluate these models and to make comparisons between them. In this paper we first summarize the work that has been done in image quality modeling. We then select two of the leading image quality models, the Daly Visible Differences Predictor and the Sarnoff Visual Discrimination Model, for further study. We begin by describing our implementation, which was done from the published papers, of each of the models. We next discuss the similarities and the differences between the two models. The paper ends with a summary of the important advantages of each approach. The comparison of these two models is presented in the context of our research interests which are image quality evaluation for both computer imaging and computer graphics tasks. The paper includes illustrations drawn from these two areas.