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The Laplacian pyramid is ubiquitous for decomposing images into multiple scales and is widely used for image analysis. However, because it is constructed with spatially invariant Gaussian kernels, the Laplacian pyramid is widely believed as being unable to represent edges well and as being ill-suited for edge-aware operations such as edge-preserving(More)
Taking multiple exposures is a well-established approach both for capturing high dynamic range (HDR) scenes and for noise reduction. But what is the optimal set of photos to capture? The typical approach to HDR capture uses a set of photos with geometrically-spaced exposure times, at a fixed ISO setting (typically ISO 100 or 200). By contrast, we show that(More)
Capturing multiple photos at different focus settings is a powerful approach for reducing optical blur, but how many photos should we capture within a fixed time budget? We develop a framework to analyze optimal capture strategies balancing the tradeoff between defocus and sensor noise, incorporating uncertainty in resolving scene depth. We derive analytic(More)
We present confocal stereo, a new method for computing 3D shape by controlling the focus and aperture of a lens. The method is specifically designed for reconstructing scenes with high geometric complexity or fine-scale texture. To achieve this, we introduce the confocal constancy property, which states that as the lens aperture varies, the pixel intensity(More)
Standard camera. We adopt a classic defocus model for the standard camera [10] that also accounts for diffraction. For a given DOF sub-interval [d 1 , d 2 ] we focus at 2d1d2 d1+d2 , to equalize defocus blur at the endpoints. Coded aperture camera [13, 22]. We simulated a 7×7 mask blocking half the light, optimized using the objective in [22]. We focus the(More)
It is straightforward to extend our approach to incorporate thermal noise, due to the release of electrons from thermal energy the electronics. This effect can be modeled by the addition of dark current, D, to the radiant power from the scene (Fig. 1), For a given temperature, thermal noise is largely systematic , so we assume that it can be calibrated on a(More)
Depth of field (DOF), the range of scene depths that appear sharp in a photograph, poses a fundamental tradeoff in photography---wide apertures are important to reduce imaging noise, but they also increase defocus blur. Recent advances in computational imaging modify the acquisition process to extend the DOF through deconvolution. Because deconvolution(More)
This paper considers the problem of reconstructing visually realistic 3D models of fire from a very small set of simultaneous views (even two). By modeling fire as a semi-transparent 3D density field, we show that fire reconstruction is equivalent to a severely under-constrained computerized tomography problem, for which traditional methods break down. Our(More)