Please note: This master’s thesis presentation will take place in DC 3317.
Frank Fan, Master’s candidate
David R. Cheriton School of Computer Science
Supervisor: Professor Gladimir Baranoski
Chlorophyll is the most important pigment for the sustainability of life on the planet. Its light absorbing properties, besides being directly associated with the green colouration of plants, play a key role in the photosynthesis process. These properties can also elicit fluorescence, a complex phenomenon leading to striking material appearance changes. Accordingly, its predictive simulation can strengthen the fidelity of realistic image synthesis frameworks, notably those targeting chlorophyll-containing materials. Moreover, the predictive visualization of chlorophyll fluorescence can lend itself to interdisciplinary applications in related areas such as botany, ecology, remote sensing and photonics. Despite these aspects, chlorophyll fluorescence remains relatively overlooked in the computer graphics literature, with related works accounting for it as a complementary rendering component tied to visible light stimulus.
In this thesis, we introduce a biophysically-based framework for the simulation and visualization of the chlorophyll fluorescence elicited by light excitation in the ultraviolet and visible spectral domains. It employs an algorithmic approach, centered on the use of fluorescent spectroscopy principles, that can be employed to the rendering and investigation of other fluorescent materials. We assess the proposed framework’s predictive capabilities through the rendering of images depicting fundamental qualitative traits verified in actual observations of chlorophyll fluorescence. We also demonstrate its effectiveness and applicability in realistic image synthesis through sequences of images depicting chlorophyll solutions under various experimental characterizations and illumination conditions.