A spectrally based framework for realistic image synthesis

Realistic image synthesis provides principles and techniques for creating realistic imagery based on models of real-world objects and behaviors. It has widespread applications in 3D design, computer animation, and scientific visualization. While it is common to describe light and objects in terms of colors, this approach is not sufficiently accurate and cannot render many spectral phenomena such as interference and diffraction. Many researchers have explored spectral rendering and proposed several methods for spectral representation, but none satisfy all representation criteria such as accuracy, compactness and efficiency. Furthermore, previous studies have focused on distinct behaviors of natural phenomena but few on their commonality and generality, and it is difficult to combine existing algorithms to simulate complex processes. This thesis proposes solutions to these problems within a spectrum-based rendering framework. The pipeline begins by loading spectra from a database to specify light sources and objects, then generates a spectral image based on local and global illumination models, projects the spectral image into a CIE image, and finally converts the CIE image into an RGB image for display or a CIELab image for evaluation. In spite of omitting the light phase information, it is shown that this approach suffices to generate all optical effects important for realistic image synthesis. As components of the new framework, a heuristic method is proposed for deriving spectra from colors and an error metric is provided for evaluating synthesized images. The new spectral representation proposed in this thesis is called the composite model. Its key point is to decompose any spectrum into a smooth background and a collection of spikes. The smooth part can be represented by Fourier coefficients and a spike by its location and height. A re-sampling technique is proposed to improve performance. Based upon the characteristics of human perception, the sufficiency of a low-dimensional representation is shown analytically. This model improves upon existing methods with aspect to accuracy, compactness and efficiency, and offers an effective vehicle for rendering optical effects involving spiky spectra. Using the proposed framework and composite spectral model, this thesis develops new illumination models for rendering a number of optical effects including dispersion, interference, diffraction, fluorescence, and volume absorption. The rendered images closely correspond to their real-world counterparts. Overall, this thesis improves realistic image synthesis by expanding its rendering capabilities. It may serve as a basis for a more sophisticated rendering environment for high-quality computer image generation.