Abstract: A method for deblurring a target image includes receiving a burst of images that includes the target image; partitioning respective images of the burst of images into respective patches; converting, to a frequency domain, the respective patches into respective transform patches; selecting a first set of corresponding transform patches from the respective transform patches, where the first set of the corresponding transform patches includes a respective transform patch for a respective image of the burst of images; obtaining, using a neural network, respective weight maps for the corresponding transform patches; obtaining a deblurred transform patch by combining the first set of corresponding transform patches using the respective weight maps; obtaining a first deblurred patch by converting the deblurred transform patch to a pixel domain; and obtaining a deblurred image of the target image using the first deblurred patch.

Abstract: Detecting a pattern in an image by receiving the image of a pattern and storing the image in a memory, where the pattern is composed of shapes that have geometrical properties that are invariant under near projective transforms. In some embodiments the process detects shapes in the image using the geometrical properties of the shapes, determines the alignment of the various shapes, and, corresponds or matches the shapes in the image with the shapes in the pattern. This pattern detection process may be used for calibration or distortion correction in optical devices.

Abstract: Detecting a pattern in an image by receiving the image of a pattern and storing the image in a memory, where the pattern is composed of shapes that have geometrical properties that are invariant under near projective transforms. In some embodiments the process detects shapes in the image using the geometrical properties of the shapes, determines the alignment of the various shapes, and, corresponds or matches the shapes in the image with the shapes in the pattern. This pattern detection process may be used for calibration or distortion correction in optical devices.

Abstract: Detecting a pattern in an image by receiving the image of a pattern and storing the image in a memory, where the pattern is composed of shapes that have geometrical properties that are invariant under near projective transforms. In some embodiments the process detects shapes in the image using the geometrical properties of the shapes, determines the alignment of the various shapes, and, corresponds or matches the shapes in the image with the shapes in the pattern. This pattern detection process may be used for calibration or distortion correction in optical devices.

Abstract: Detecting a pattern in an image by receiving the image of a pattern and storing the image in a memory, where the pattern is composed of shapes that have geometrical properties that are invariant under near projective transforms. In some embodiments the process detects shapes in the image using the geometrical properties of the shapes, determines the alignment of the various shapes, and, corresponds or matches the shapes in the image with the shapes in the pattern. This pattern detection process may be used for calibration or distortion correction in optical devices.

Abstract: A method for calibrating an imaging instrument, possibly located on an aircraft or satellite, is described. According to the method, an image acquired by the instrument is ortho-rectified, and then co-registered and correlated with a reference image. In this way, ground disparities between the acquired image and the reference image are measured. Updated instrument pointing directions that correct for the disparities measured are then determined and adopted as corrective calibrations for the distortions of the instrument.

Abstract: Detecting a pattern in an image by receiving the image of a pattern and storing the image in a memory, where the pattern is composed of shapes that have geometrical properties that are invariant under near projective transforms. In some embodiments the process detects shapes in the image using the geometrical properties of the shapes, determines the alignment of the various shapes, and, corresponds or matches the shapes in the image with the shapes in the pattern. This pattern detection process may be used for calibration or distortion correction in optical devices.

Abstract: A method for calibrating an imaging instrument, possibly located on an aircraft or satellite, is described. According to the method, an image acquired by the instrument is ortho-rectified, and then co-registered and correlated with a reference image. In this way, ground disparities between the acquired image and the reference image are measured. Updated instrument pointing directions that correct for the disparities measured are then determined and adopted as corrective calibrations for the distortions of the instrument.