Abstract: An image registration system for aligning first and second images. The novel system includes a first system for extracting a region of interest (ROI) from each image and a second system for coarsely aligning the regions of interest. The first system determines the size and location of the ROI based on the number of features contained within the region. The size of the ROI is enlarged until a number of features contained in the ROI is larger than a predetermined lower bound or until the size is greater than a predetermined upper bound. The second system computes a cross-correlation on the regions of interest using a plurality of transforms to find a coarse alignment transform having a highest correlation. The image registration system may also include a third system for performing sub-pixel alignment on the regions of interest.

Abstract: The technology described herein includes integration of image frames. The integration of image frames includes determining a sharpness metric for each image frame in a plurality of image frames. The sharpness metric is indicative of at least one of edge content and an edge size of the image frame. The integration of image frames further includes determining a noise metric for each image frame in the plurality of image frames. The noise metric is indicative of a variation in brightness or color in the image frame. The integration of image frames further includes determining a jitter metric for each image frame in the plurality of image frames. The jitter metric is indicative of spatial shifts between the image frame and other image frames in the plurality of image frames. The integration of image frames further includes generating an integrated image frame from one or more of the plurality of image frames based on the sharpness metric, the noise metric, and the jitter metric.

Abstract: An image registration system for aligning first and second images. The novel system includes a first system for extracting a region of interest (ROI) from each image and a second system for coarsely aligning the regions of interest. The first system determines the size and location of the ROI based on the number of features contained within the region. The size of the ROI is enlarged until a number of features contained in the ROI is larger than a predetermined lower bound or until the size is greater than a predetermined upper bound. The second system computes a cross-correlation on the regions of interest using a plurality of transforms to find a coarse alignment transform having a highest correlation. The image registration system may also include a third system for performing sub-pixel alignment on the regions of interest.

Abstract: An image registration system for aligning first and second images. The novel system includes a first system for extracting a region of interest (ROI) from each image and a second system for coarsely aligning the regions of interest. The first system determines the size and location of the ROI based on the number of features contained within the region. The size of the ROI is enlarged until a number of features contained in the ROI is larger than a predetermined lower bound or until the size is greater than a predetermined upper bound. The second system computes a cross-correlation on the regions of interest using a plurality of transforms to find a coarse alignment transform having a highest correlation. The image registration system may also include a third system for performing sub-pixel alignment on the regions of interest.

Abstract: The technology described herein includes integration of image frames. The integration of image frames includes determining a sharpness metric for each image frame in a plurality of image frames. The sharpness metric is indicative of at least one of edge content and an edge size of the image frame. The integration of image frames further includes determining a noise metric for each image frame in the plurality of image frames. The noise metric is indicative of a variation in brightness or color in the image frame. The integration of image frames further includes determining a jitter metric for each image frame in the plurality of image frames. The jitter metric is indicative of spatial shifts between the image frame and other image frames in the plurality of image frames. The integration of image frames further includes generating an integrated image frame from one or more of the plurality of image frames based on the sharpness metric, the noise metric, and the jitter metric.

Abstract: An image registration system for aligning first and second images. The novel system includes a first system for extracting a region of interest (ROI) from each image and a second system for coarsely aligning the regions of interest. The first system determines the size and location of the ROI based on the number of features contained within the region. The size of the ROI is enlarged until a number of features contained in the ROI is larger than a predetermined lower bound or until the size is greater than a predetermined upper bound. The second system computes a cross-correlation on the regions of interest using a plurality of transforms to find a coarse alignment transform having a highest correlation. The image registration system may also include a third system for performing sub-pixel alignment on the regions of interest.

Abstract: An image processing system and method. The image processing system acquires a first set of scan lines in at first field of image data and a second set of scan lines in a second field of image data; the second set of scan lines are interlaced relative to the first set of scan lines and performs a line by line correlation therebetween to provide an error signal or value. The first and second fields are buffered and coupled to a line-to-line correlator. The error signal is used to adjust either the first or the second set of scan lines to correct for skew or blur in the second field of image data.

Abstract: An image registration system for aligning first and second images. The novel system includes a first system for extracting a region of interest (ROI) from each image and a second system for coarsely aligning the regions of interest. The first system determines the size and location of the ROI based on the number of features contained within the region. The size of the ROI is enlarged until a number of features contained in the ROI is larger than a predetermined lower bound or until the size is greater than a predetermined upper bound. The second system computes a cross-correlation on the regions of interest using a plurality of transforms to find a coarse alignment transform having a highest correlation. The image registration system may also include a third system for performing sub-pixel alignment on the regions of interest.