Method and apparatus to correct digital image blur due to motion of subject or imaging device
First Claim
1. A method, comprising:
- a recording medium in an imager recording image data that represents an image;
a motion sensor measuring motion information while the recording medium is capturing the image data, wherein the motion information indicates motion of the imager;
a processor determining a transfer function based on the motion information;
the processor determining an initial state for an inverse transfer function;
the processor updating the inverse transfer function using an iterative technique, wherein the iterative technique includes, for each of a plurality of iterations;
determining a first estimate of the image data based on the inverse transfer function and a finite impulse response (FIR) filter;
determining a second estimate of the image data based on the first estimate of the image data and the transfer function;
determining an estimation error parameter by comparing the second estimate of the image data and the image data; and
updating the inverse transfer function based on the estimation error parameter and a step-size parameter;
the processor determining a deconvolution filter based on the inverse transfer function; and
the processor filtering the image data using the deconvolution filter.
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Abstract
Signal processing techniques are applied to digital image data to remove the distortion caused by motion of the camera, or the movement of the subject being photographed, or defective optics, or optical distortion from other sources. When the image is captured, the effect of relative motion between the camera and the subject is that it transforms the true image into a blurred image according to a 2-dimensional transfer function. The 2-dimensional transfer function representing the motion is derived using blind estimation techniques or by using information from sensors that detect the motion. The transfer function is inverted and used to define a corrective filter. The filter is applied to the image and the blur due to the motion is removed, restoring the correct image. Another embodiment uses the transfer function to avoid blur by combining multiple consecutive images taken at a fast shutter speed.
57 Citations
12 Claims
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1. A method, comprising:
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a recording medium in an imager recording image data that represents an image; a motion sensor measuring motion information while the recording medium is capturing the image data, wherein the motion information indicates motion of the imager; a processor determining a transfer function based on the motion information; the processor determining an initial state for an inverse transfer function; the processor updating the inverse transfer function using an iterative technique, wherein the iterative technique includes, for each of a plurality of iterations; determining a first estimate of the image data based on the inverse transfer function and a finite impulse response (FIR) filter; determining a second estimate of the image data based on the first estimate of the image data and the transfer function; determining an estimation error parameter by comparing the second estimate of the image data and the image data; and updating the inverse transfer function based on the estimation error parameter and a step-size parameter; the processor determining a deconvolution filter based on the inverse transfer function; and the processor filtering the image data using the deconvolution filter. - View Dependent Claims (2, 3, 4, 5, 6)
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7. An apparatus, comprising:
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a recording medium configured to record image data; a motion sensor configured to measure motion information while the recording medium is capturing the image data, wherein the motion information indicates motion of the apparatus; and a processor configured; to determine a transfer function based on the motion information; to determine an initial state for an inverse transfer function; to update the inverse transfer function using an iterative technique, wherein the iterative technique includes, for each of a plurality of iterations; determining an estimate of the image data based on the inverse transfer function and a finite impulse response (FIR) filter; determining a second estimate of the image data based on the estimate of the image data and the transfer function; determining an estimation error parameter by comparing the second estimate of the image data and the image data; and updating the inverse transfer function based on the estimation error parameter and a step-size parameter; to determine a deconvolution filter based on the inverse transfer function; and to filter the image data using the deconvolution filter. - View Dependent Claims (8, 9, 10, 11, 12)
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Specification