Abstract: A pair of cameras having an overlapping field of view is aligned based on images captured by image sensors of the pair of cameras. A pixel shift is identified between the images. Based on the identified pixel shift, a calibration is applied to one or both of the pair of cameras. To determine the pixel shift, the camera applies correlation methods including edge matching. Calibrating the pair of cameras may include adjusting a read window on an image sensor. The pixel shift can also be used to determine a time lag, which can be used to synchronize subsequent image captures.

Abstract: A pair of cameras having an overlapping field of view is aligned based on images captured by image sensors of the pair of cameras. A pixel shift is identified between the images. Based on the identified pixel shift, a calibration is applied to one or both of the pair of cameras. To determine the pixel shift, the camera applies correlation methods including edge matching. Calibrating the pair of cameras may include adjusting a read window on an image sensor. The pixel shift can also be used to determine a time lag, which can be used to synchronize subsequent image captures.

Abstract: A method for use in medical imaging of a patient including, with the patient immobilized with respect to an imaging reference frame, acquiring first digital imaging information including a first region of interest using a first imaging modality; processing the first digital imaging information to identify a feature for analysis; and using a second imaging modality to acquire targeted second imaging information for a second region of interest, the second region of interest corresponding to a subset of the first region of interest, wherein the second region of interest includes the feature for analysis.

Abstract: A pair of cameras having an overlapping field of view is aligned based on images captured by image sensors of the pair of cameras. A pixel shift is identified between the images. Based on the identified pixel shift, a calibration is applied to one or both of the pair of cameras. To determine the pixel shift, the camera applies correlation methods including edge matching. Calibrating the pair of cameras may include adjusting a read window on an image sensor. The pixel shift can also be used to determine a time lag, which can be used to synchronize subsequent image captures.

Abstract: A pair of cameras having an overlapping field of view is aligned based on images captured by image sensors of the pair of cameras. A pixel shift is identified between the images. Based on the identified pixel shift, a calibration is applied to one or both of the pair of cameras. To determine the pixel shift, the camera applies correlation methods including edge matching. Calibrating the pair of cameras may include adjusting a read window on an image sensor. The pixel shift can also be used to determine a time lag, which can be used to synchronize subsequent image captures.

Abstract: A pair of cameras having an overlapping field of view is aligned based on images captured by image sensors of the pair of cameras. A pixel shift is identified between the images. Based on the identified pixel shift, a calibration is applied to one or both of the pair of cameras. To determine the pixel shift, the camera applies correlation methods including edge matching. Calibrating the pair of cameras may include adjusting a read window on an image sensor. The pixel shift can also be used to determine a time lag, which can be used to synchronize subsequent image captures.

Abstract: An electronic device may have a camera module. The camera module may capture images having an initial depth of field. The electronic device may receive user input selecting a focal plane and an effective f-stop for use in producing a modified image with a reduced depth of field. The electronic device may include image processing circuitry that selectively blurs various regions of a captured image, with each region being blurred to an amount that varies with distance to the user selected focal plane and in response to the user selected effective f-stop (e.g., a user selected level of depth of field).

Abstract: A pair of cameras having an overlapping field of view is aligned based on images captured by image sensors of the pair of cameras. A pixel shift is identified between the images. Based on the identified pixel shift, a calibration is applied to one or both of the pair of cameras. To determine the pixel shift, the camera applies correlation methods including edge matching. Calibrating the pair of cameras may include adjusting a read window on an image sensor. The pixel shift can also be used to determine a time lag, which can be used to synchronize subsequent image captures.

Abstract: A pair of cameras having an overlapping field of view is aligned based on images captured by image sensors of the pair of cameras. A pixel shift is identified between the images. Based on the identified pixel shift, a calibration is applied to one or both of the pair of cameras. To determine the pixel shift, the camera applies correlation methods including edge matching. Calibrating the pair of cameras may include adjusting a read window on an image sensor. The pixel shift can also be used to determine a time lag, which can be used to synchronize subsequent image captures.

Abstract: A pair of cameras having an overlapping field of view is aligned based on images captured by image sensors of the pair of cameras. A pixel shift is identified between the images. Based on the identified pixel shift, a calibration is applied to one or both of the pair of cameras. To determine the pixel shift, the camera applies correlation methods including edge matching. Calibrating the pair of cameras may include adjusting a read window on an image sensor. The pixel shift can also be used to determine a time lag, which can be used to synchronize subsequent image captures.

Abstract: A system of stereo imagers, including image processing units and methods of blurring an image, is presented. The image is received from an image sensor. For each pixel of the image, a depth filter component is determined based on a focal area of the image and a depth map associated with the image. For each pixel of the image, a trilateral filter is generated that includes a spatial filter component, a range filter component and the depth filter component. The respective trilateral filter is applied to corresponding pixels of the image to blur the image outside of the focal area. A refocus area or position may be determined by imaging geometry or may be selected manually via a user interface.

Abstract: A pair of cameras having an overlapping field of view is aligned based on images captured by image sensors of the pair of cameras. A pixel shift is identified between the images. Based on the identified pixel shift, a calibration is applied to one or both of the pair of cameras. To determine the pixel shift, the camera applies correlation methods including edge matching. Calibrating the pair of cameras may include adjusting a read window on an image sensor. The pixel shift can also be used to determine a time lag, which can be used to synchronize subsequent image captures.

Abstract: A method of suppressing a dark halo in an imager includes the steps of: extracting an edge value from an image; determining a chroma zone associated with the edge value extracted from the image; and modifying the edge value based on the chroma zone associated with the extracted edge value. The modified edge value from the imager is then provided to a user. The step of determining the chroma zone includes determining a chroma value of Cr and Cb in a Y-Cr-Cb color space; and modifying the edge value includes multiplying the edge value by a predetermined gain value, k, depending on the chroma value of Cr and Cb. If the value of Cr is greater than zero, then the gain value k is set close to zero, in order to suppress the dark halo in the modified edge value. On the other hand, if the value of Cr is less than zero, then the gain value k is set close to one, in order to sharpen the modified edge value in the image.

Abstract: A method of processing an image includes the steps of separating an image into multiple color channels, and dividing the image into multiple zones, in which each zone includes a sub-array of pixels. The method then calculates a color shading profile for each zone. The color shading profile is calculated as a linear function, typically a straight line. If a linear function cannot be determined for that zone, the method interprets a function for that zone using the nearest zone neighbors. The method corrects the color shading using the functions calculated for the respective zones.

Abstract: A method for use in medical imaging of a patient including, with the patient immobilized with respect to an imaging reference frame, acquiring first digital imaging information including a first region of interest using a first imaging modality; processing the first digital imaging information to identify a feature for analysis; and using a second imaging modality to acquire targeted second imaging information for a second region of interest, the second region of interest corresponding to a subset of the first region of interest, wherein the second region of interest includes the feature for analysis.

Abstract: A system of stereo imagers, including image processing units and methods of blurring an image, is presented. The image is received from an image sensor. For each pixel of the image, a depth filter component is determined based on a focal area of the image and a depth map associated with the image. For each pixel of the image, a trilateral filter is generated that includes a spatial filter component, a range filter component and the depth filter component. The respective trilateral filter is applied to corresponding pixels of the image to blur the image outside of the focal area. A refocus area or position may be determined by imaging geometry or may be selected manually via a user interface.

Abstract: A method for use in medical imaging of a patient including, with the patient immobilized with respect to an imaging reference frame, acquiring first digital imaging information including a first region of interest using a first imaging modality; processing the first digital imaging information to identify a feature for analysis; and using a second imaging modality to acquire targeted second imaging information for a second region of interest, the second region of interest corresponding to a subset of the first region of interest, wherein the second region of interest includes the feature for analysis.

Abstract: A method of suppressing a dark halo in an imager includes the steps of: extracting an edge value from an image; determining a chroma zone associated with the edge value extracted from the image; and modifying the edge value based on the chroma zone associated with the extracted edge value. The modified edge value from the imager is then provided to a user. The step of determining the chroma zone includes determining a chroma value of Cr and Cb in a Y-Cr-Cb color space; and modifying the edge value includes multiplying the edge value by a predetermined gain value, k, depending on the chroma value of Cr and Cb. If the value of Cr is greater than zero, then the gain value k is set close to zero, in order to suppress the dark halo in the modified edge value. On the other hand, if the value of Cr is less than zero, then the gain value k is set close to one, in order to sharpen the modified edge value in the image.

Abstract: A method of processing an image includes the steps of separating an image into multiple color channels, and dividing the image into multiple zones, in which each zone includes a sub-array of pixels. The method then calculates a color shading profile for each zone. The color shading profile is calculated as a linear function, typically a straight line. If a linear function cannot be determined for that zone, the method interprets a function for that zone using the nearest zone neighbors. The method corrects the color shading using the functions calculated for the respective zones.

Abstract: A method for image linear structure detection in medical imaging. The method includes locating microcalcification (mcc) candidate spots in a mammographic image; forming candidate clusters; assigning ranks to the candidate clusters; identifying linear structures in the neighborhood where the candidate clusters reside; and altering the ranks of the candidate clusters for which linear structures have been identified in the neighborhood.