Abstract:

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 ill-posed 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 motion-blur removal including extremely large 
motions, textured backgrounds and partial occluders.

Top left shows image of a fast moving taxi captured using our new camera. Bottom left shows the rectified image to make motion lines 
parallel to scan lines. An approximate cutout of the blurred object is shown in top right. The deblurred image obtained by solving a 
linear system is shown in bottom right. Note that all high frequencies are recovered and there are no deconvolution artifacts.


Key idea and differences with previous methods:

Motion deblurring is an ill-posed problem. The relative motion between camera and the scene results in a blurred image in
which high frequencies are lost, due to which deblurring results in increased noise, ringing and other artifacts. Note that this is
independent of the deblurring algorithm used. As soon as the image is captured, high frequencies are lost and the damage is done.

In this paper, we propose a novel coded exposure camera and show that by fluttering the shutter in a single exposure, one can
retain high frequencies. The deblurring then become a well-posed problem. Our approach is thus fundamentally different from other 
deblurring algorithms. In fact, we use the simplest possible deconvolution approach: solving a linear system AX=B to recover
the sharp image X from the blurred image B and show high quality results with large motion blurs (~300 pixels) with no ringing and 
deconvolution artifacts. The change in hardware amounts to putting an external ferro-electric shutter in front of the lens, 
synchronized with the start of the exposure time and can be done on any off the shelf digital camera.

Comparison of Short Exposure, Traditional Camera, and Coded Exposure Camera

Our portable prototype camera Picture taken with a traditional camera Picture taken with our camera The above two images shows comparison of images taken with a traditional camera and coded exposure camera. A bright LED (light emitting diode) is moved rapidly in front of the camera by a person. For traditional camera, the image of LED is a continuous smear (on left). For coded exposure, due to fluttering of the shutter, the smear becomes discontinuous preserving high frequencies (on right).

Additional Results
	Outdoor Taxi
	Comparisons with Short Exposure and Traditional Camera
	License Plate Retrieval from Blurred Image
	



Related Papers:

Resolving Objects at Higher Resolution from a Single Motion-Blurred Image, CVPR 2007
Dappled Photography: Mask Enahnced Cameras for Heterodyned Light Fields and Coded Aperture Refocusing, SIGGRAPH 2007