Abstract:
Methods of computational photography transform raw data from an image sensor into an image, improve image quality with dedicated hardware, or provide capability beyond film-based photography. With the current success of 3-dimensional display technology, binocular stereo cameras become increasingly popular for data recording. Taking advantage of depth hints provided by stereo images, computational photography may go further, beyond just 3-dimensional visualisation of recorded data. This thesis presents the simulation of three depth-aware artistic effects using stereo vision, briefly addressed by fog, bokeh, or star effects. We aim at achieving related artistic effects in some comfortable and controllable ways. Fog is an important factor in photography with a special aesthetic, emotional, or compositional meaning. We present a fog-effect-simulation method with optional interaction for control purposes. Besides homogeneous fog, we provide three tools to control the density of the fog media. Thus, various kinds of heterogeneous atmospheric effects can be simulated. Bokeh, a sought-after photo rendering style of out-of-focus blur, typically aims at an aesthetic quality which is not available to low-end consumer grade cameras due to the lens design. We present a bokeh-effect simulation method with useradjustable apertures sizes or shapes. Over-exposed regions are recovered according to depth information before bokeh rendering. We also simulate swirly bokeh, also known as cat-eye effect. Night-time photos featuring compelling lighting show sometimes star patterns around highlights, known as star effect in photography. Such star patterns are often essential for defining the aesthetic meaning of night-time photographs. We present a star-effect simulation method based on self-calibrated stereo vision. We render star patterns with a chosen input texture. We use depth information as provided by a stereo matcher, and this information is typically not perfect for computational photography tasks where visual quality is required rather than detailed depth accuracy. The thesis also discusses different stereo-refinement methods that fit the requirements of each of the three mentioned tasks of computational photogrammetry.