Coded exposure photography: motion deblurring using fluttered shutter

In a conventional single-exposure photograph, moving objects or moving cameras cause motion blur. The exposure time defines a temporal box filter that smears the moving object across the image by convolution. This box filter destroys important high-frequency spatial details so that deblurring via deconvolution becomes an illposed problem. Rather than leaving the shutter open for the entire exposure duration, we ”flutter ” the camera’s shutter open and closed during the chosen exposure time with a binary pseudo-random sequence. The flutter changes the box filter to a broad-band filter that preserves high-frequency spatial details in the blurred image and the corresponding deconvolution becomes a well-posed problem. We demonstrate that manually-specified point spread functions are sufficient for several challenging cases of motionblur removal including extremely large motions, textured backgrounds and partial occluders. ACM Transactions o Graphics (TOG

Two Methods for Display of High Contrast Images

High contrast images are common in night scenes and other scenes that include dark shadows and bright light sources. These scenes are difficult to display because their contrasts greatly exceed the range of most display devices for images. As a result, the image contrasts are compressed or truncated, obscuring subtle textures and details. Humans view and understand high contrast scenes easily, ``adapting'' their visual response to avoid compression or truncation with no apparent loss of detail. By imitating some of these visual adaptation processes, we developed two methods for the improved display of high contrast images. The first builds a display image from several layers of lighting and surface properties. Only the lighting layers are compressed, drastically reducing contrast while preserving much of the image detail. This method is practical only for synthetic images where the layers can be retained from the rendering process. The second method interactively adjusts the displayed image to preserve local contrasts in a small ``foveal'' neighborhood. Unlike the first method, this technique is usable on any image and includes a new tone reproduction operator. Both methods use a sigmoid function for contrast compression. This function has no effect when applied to small signals but compresses large signals to fit within an asymptotic limit. We demonstrate the effectiveness of these approaches by comparing processed and unprocessed images

Three methods of detail-preserving contrast reduction for displayed images

Ph.D.Greg Tur

Why I want a Gradient Camera

We propose a camera that measures static gradients instead of static intensities. Quantizing sensed intensity differences between adjacent pixel values permits an ordinary A/D converter to measure detailed high contrast (HDR) scenes. We measure alternating `cliques' of sensors (small groups) that locally determine their own best exposure, and reconstruct the image using a Poisson solver. This intrinsically differential design suppresses common-mode noise, hides and smoothes quantization, and can correct for its own saturated sensors. Simulations demonstrate these capabilities in side-by-side comparisons

Microsoft Corp.

This article introduces quadrature prefiltering, an accurate, efficient, and fairly simple algorithm for prefiltering polygons for scanline rendering. It renders very high quality images at reasonable cost, strongly suppressing aliasing artifacts. For equivalent RMS error, quadrature prefiltering is significantly faster than either uniform or jittered supersampling. Quadrature prefiltering is simple to implement and space-efficient; it needs only a small twodimensional lookup table, even when computing nonradially symmetric filter kernels. Previous algorithms have required either three-dimensional tables or a restriction to radially symmetric filter kernels. Though only slightly more complicated to implement than the widely used box prefiltering method, quadrature prefiltering can generate images with much less visible aliasing artifacts