Abstract-Relightable photographs are alternatives to traditional photographs as they provide a richer viewing experience. However, the complex acquisition systems of existing techniques have restricted its usage to specialized setups. We introduce an easy-to-use and affordable solution for using smartphones to acquire the reflectance of paintings and similar almost-planar objects like tablets, engravings and textile. Our goal is to enable interactive relighting of such artifacts by everyone. In our approach, we non-uniformly sample the reflectance functions by moving the LED light of a smartphone and simultaneously tracking the position of the smartphone by using its camera. We then propose a compressive-sensing based approach for reconstructing the light transport matrix from the non-uniformly sampled data. As shown with experiments, we accurately reconstruct the light transport matrix that can then be used to create relightable photographs.Index Terms-Light transport matrix, computational relighting, image based relighting, compressive sensing, non-uniform sampling, mobile imaging.
The spatial frequency response (SFR) is one of the most important and unbiased image quality measures of a digital camera. It evaluates to which extent a lens/sensor combination can resolve scene details. In this paper, we propose a simple and practical method to measure the SFR of microlensbased light field cameras. The particularity of such cameras resides in their ability to capture both spatial and angular information of the incoming light field thanks to an array of microlenses located in front of the sensor. Existing methods for measuring the SFR of conventional cameras are thus no longer applicable as the interaction between the main lens and the micro-lenses results in different resolving powers over the image plane that depend on the scene depths. By using a 3-dimensional target made of vertical lines printed on an inclined planar surface, we are able to measure the SFR across multiple depths in a single exposure. Our method allows SFR measurements from the raw light field itself as captured by the camera, and is thus independent of subsequent post-processing algorithms such as image reconstruction, digital refocusing or depth estimation. Our experimental results are consistent with theoretical bounds and reproducible.
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