Abstract: Methods and systems for image processing are provided. A method for processing images of a scene includes receiving image data of a reference and a current frame; generating N motion vectors that describe motion of the image data within the scene by computing a correlation function on the reference and current frames at each of N registration points; registering the current frame based on the N motion vectors to produce a registered current frame; and updating the image data of the scene based on the registered current frame. Optionally, registered frames may be oversampled. Techniques for generating the N motion vectors according to roll, zoom, shift and optical flow calculations, updating image data of the scene according to switched and intermediate integration approaches, re-introducing smoothed motion into image data of the scene, re-initializing the process, and processing images of a scene and moving target within the scene are provided.

Abstract: Methods and systems for image processing are provided. A method for processing images of a scene includes receiving image data of a reference and a current frame; generating N motion vectors that describe motion of the image data within the scene by computing a correlation function on the reference and current frames at each of N registration points; registering the current frame based on the N motion vectors to produce a registered current frame; and updating the image data of the scene based on the registered current frame. Optionally, registered frames may be oversampled. Techniques for generating the N motion vectors according to roll, zoom, shift and optical flow calculations, updating image data of the scene according to switched and intermediate integration approaches, re-introducing smoothed motion into image data of the scene, re-initializing the process, and processing images of a scene and moving target within the scene are provided.

Abstract: Methods and systems for image processing are provided. A method for processing images of a scene includes receiving image data of a reference and a current frame; generating N motion vectors that describe motion of the image data within the scene by computing a correlation function on the reference and current frames at each of N registration points; registering the current frame based on the N motion vectors to produce a registered current frame; and updating the image data of the scene based on the registered current frame. Optionally, registered frames may be oversampled. Techniques for generating the N motion vectors according to roll, zoom, shift and optical flow calculations, updating image data of the scene according to switched and intermediate integration approaches, re-introducing smoothed motion into image data of the scene, re-initializing the process, and processing images of a scene and moving target within the scene are provided.

Abstract: Methods and systems for image processing are provided. A method for processing images of a scene includes receiving image data of a reference and a current frame; generating N motion vectors that describe motion of the image data within the scene by computing a correlation function on the reference and current frames at each of N registration points; registering the current frame based on the N motion vectors to produce a registered current frame; and updating the image data of the scene based on the registered current frame. Optionally, registered frames may be oversampled. Techniques for generating the N motion vectors according to roll, zoom, shift and optical flow calculations, updating image data of the scene according to switched and intermediate integration approaches, re-introducing smoothed motion into image data of the scene, re-initializing the process, and processing images of a scene and moving target within the scene are provided.

Abstract: Methods and systems for image processing are provided. A method for processing images of a scene includes receiving image data of a reference and a current frame; generating N motion vectors that describe motion of the image data within the scene by computing a correlation function on the reference and current frames at each of N registration points; registering the current frame based on the N motion vectors to produce a registered current frame; and updating the image data of the scene based on the registered current frame. Optionally, registered frames may be oversampled. Techniques for generating the N motion vectors according to roll, zoom, shift and optical flow calculations, updating image data of the scene according to switched and intermediate integration approaches, re-introducing smoothed motion into image data of the scene, re-initializing the process, and processing images of a scene and moving target within the scene are provided.

Abstract: A method and apparatus for processing imagery using images acquired via any known Electro-Optical (EO) system. In accordance with exemplary embodiments of the present invention, a first frame of data is selected as a template frame (e.g., a given frame). A second frame of data can be captured using the EO system. At least a portion of the second frame can be correlated with the template frame to generate a shift vector. The second frame can then be registered with the template frame by interpolating the second frame using the shift vector and re-sampling at least a portion of the second frame to produce a registered frame. The template frame can also be re-sampled. The registered frame and the re-sampled template frame can then be combined to generate an averaged frame. The averaged frame can be spatially filtered to enhance edges within the averaged frame.

Abstract: A method of processing image data comprises obtaining a set of weighting coefficients to be used in calculating replacement pixel values associated with defective sensing elements of a detector array, the set of weighting coefficients including at least one negative weighting coefficient, obtaining information identifying one or more defective sensing elements of the detector array, receiving image data from the detector array, calculating a weighted average of pixel values from sensing elements adjacent to a first defective sensing element of the detector array using at least some of the weighting coefficients, and assigning the weighted average to be a replacement pixel value for the first defective sensing element. An apparatus for processing image data according to the method is also described.

Abstract: An image based autofocus method and system that includes receiving image data; monitoring and analyzing the contrast between different portions of the image data in determining the location of a target wherein the different portions of the image data contain at least one type of image pixel information and the monitoring and analyzing are performed using at least one kernel filter to determine a focus measure; adjusting a focus mechanism that is focusing on the image data; observing an image quality of the image data that has been focused; and continuously outputting an image to support an image processing frame rate and adjusting the focus mechanism to obtain an improved focus image by adjusting the focus mechanism in a positive direction, a negative direction or a zero (0) direction based upon effectuating a desired change in the observed image quality of the image data.

Abstract: Methods and systems for image processing are provided. A method for processing images of a scene includes receiving image data of a reference and a current frame; generating N motion vectors that describe motion of the image data within the scene by computing a correlation function on the reference and current frames at each of N registration points; registering the current frame based on the N motion vectors to produce a registered current frame; and updating the image data of the scene based on the registered current frame. Optionally, registered frames may be oversampled. Techniques for generating the N motion vectors according to roll, zoom, shift and optical flow calculations, updating image data of the scene according to switched and intermediate integration approaches, re-introducing smoothed motion into image data of the scene, re-initializing the process, and processing images of a scene and moving target within the scene are provided.

Abstract: A method and apparatus for processing imagery using images acquired via any known Electro-Optical (EO) system. In accordance with exemplary embodiments of the present invention, a first frame of data is selected as a template frame (e.g., a given frame). A second frame of data can be captured using the EO system. At least a portion of the second frame can be correlated with the template frame to generate a shift vector. The second frame can then be registered with the template frame by interpolating the second frame using the shift vector and re-sampling at least a portion of the second frame to produce a registered frame. The template frame can also be re-sampled. The registered frame and the re-sampled template frame can then be combined to generate an averaged frame. The averaged frame can be spatially filtered to enhance edges within the averaged frame.

Abstract: A method and apparatus for processing imagery using images acquired via any known Electro-Optical (EO) system. In accordance with exemplary embodiments of the present invention, a first frame of data is selected as a template frame (e.g., a given frame). A second frame of data can be captured using the EO system. At least a portion of the second frame can be correlated with the template frame to generate a shift vector. The second frame can then be registered with the template frame by interpolating the second frame using the shift vector and re-sampling at least a portion of the second frame to produce a registered frame. The template frame can also be re-sampled. The registered frame and the re-sampled template frame can then be combined to generate an averaged frame. The averaged frame can be spatially filtered to enhance edges within the averaged frame.

Abstract: An approach for processing image data is described. The method comprises correcting a frame of image data received from a detector using existing correction coefficients that comprise a plurality of offset coefficients corresponding to a plurality of detector elements. The method also comprises calculating an update parameter for each detector element using pixel data generated from the correction. The update parameter for a given detector element is calculated from multiple difference values determined from a given pixel value of the pixel data and multiple adjacent pixel values. The given pixel value corresponds to the given detector element. Each difference value is determined by subtracting one of the multiple adjacent pixel values from the given pixel value. The method comprises identifying offset coefficients whose existing values are to remain unchanged based upon the update parameters and changing existing values of offset coefficients other than those identified to remain unchanged.

Abstract: A method and apparatus for processing image data is described, comprising acquiring a frame of image data and compressing the dynamic range of the frame of image data using a dynamic range compression (DRC) algorithm that utilizes down-sampling, median filtering, and up-sampling. The DRC algorithm comprises down-sampling a frame of image data comprising a first array of pixels to generate a second array of pixels, applying a first median filter to the second array of pixels to generate a blurred array of pixels, up-sampling the blurred array of pixels, and removing at least a portion of low-frequency gradient data generated by previous steps from the frame of image data.

Abstract: A method and apparatus for providing corrected values of gain and level coefficients of a set of correction coefficients for a scanning detector array, such as an IR detector array, comprising a plurality of detector channels is described. First values of the gain and level coefficients can be modified using at least one frame of image data collected by the scanning detector array from out-of-focus multiple-temperature imagery. Updated values of the gain and level coefficients can be determined using a scene-based non-uniformity correction (SBNUC) routine applied to scene data corresponding to focused scene imagery. The SBNUC routine can be applied iteratively such that updated values of gain and level coefficients converge to stable values.

Abstract: A system and method are described for automatically determining the modulation transfer function (MTF) of an optical system. In accordance with exemplary embodiments of the present invention, optical information is collected from the optical system by imaging a bar target having at least one associated frequency to provide a bar target image for a first focus setting of the optical system. A first MTF of the optical system is determined for the at least one associated frequency at the first focus setting from the bar target image. The steps of collecting and determining are repeated by automatically selecting at least a second focus setting of the optical system to determine at least a second MTF for the at least one associated frequency. An MTF for the at least one associated frequency of the optical system is determined by interpolating the first and at least second MTFs.

Abstract: A method of processing image data comprises obtaining a set of weighting coefficients to be used in calculating replacement pixel values associated with defective sensing elements of a detector array, the set of weighting coefficients including at least one negative weighting coefficient, obtaining information identifying one or more defective sensing elements of the detector array, receiving image data from the detector array, calculating a weighted average of pixel values from sensing elements adjacent to a first defective sensing element of the detector array using at least some of the weighting coefficients, and assigning the weighted average to be a replacement pixel value for the first defective sensing element. An apparatus for processing image data according to the method is also described.

Abstract: An image based autofocus method and system that includes receiving image data; monitoring and analyzing the contrast between different portions of the image data in determining the location of a target wherein the different portions of the image data contain at least one type of image pixel information and the monitoring and analyzing are performed using at least one kernel filter to determine a focus measure; adjusting a focus mechanism that is focusing on the image data; observing an image quality of the image data that has been focused; and continuously outputting an image to support an image processing frame rate and adjusting the focus mechanism to obtain an improved focus image by adjusting the focus mechanism in a positive direction, a negative direction or a zero (0) direction based upon effectuating a desired change in the observed image quality of the image data.

Abstract: A window baffle assembly has a multi-element segmented window having a first surface adapted to receive at least one wavelength of radiation from an optical system, a baffle housing positioned proximate at least a portion of the first surface of the segmented window, and a plurality of baffle elements each affixed between positions on the baffle housing and offset from the first surface of the window. At least a portion of the plurality of baffle elements are in a Field of View of the optical system at an operational angle. The surface of the baffle elements are adapted to absorb at least a portion of the energy of the radiation and oriented to scatter the radiation. Each baffle element comprises a leading edge and an opposing trailing edge, the leading edge oriented toward the first surface of the window and the trailing edge oriented to point toward a central point of the optical system. A method of manufacturing a window baffle assembly is also provided.

Abstract: An approach for processing image data is described. The method comprises correcting a frame of image data received from a detector using existing correction coefficients that comprise a plurality of offset coefficients corresponding to a plurality of detector elements. The method also comprises calculating an update parameter for each detector element using pixel data generated from the correction. The update parameter for a given detector element is calculated from multiple difference values determined from a given pixel value of the pixel data and multiple adjacent pixel values. The given pixel value corresponds to the given detector element. Each difference value is determined by subtracting one of the multiple adjacent pixel values from the given pixel value. The method comprises identifying offset coefficients whose existing values are to remain unchanged based upon the update parameters and changing existing values of offset coefficients other than those identified to remain unchanged.

Abstract: A window baffle assembly has a multi-element segmented window having a first surface adapted to receive at least one wavelength of radiation from an optical system, a baffle housing positioned proximate at least a portion of the first surface of the segmented window, and a plurality of baffle elements each affixed between positions on the baffle housing and offset from the first surface of the window. At least a portion of the plurality of baffle elements are in a Field of View of the optical system at an operational angle. The surface of the baffle elements are adapted to absorb at least a portion of the energy of the radiation and oriented to scatter the radiation. Each baffle element comprises a leading edge and an opposing trailing edge, the leading edge oriented toward the first surface of the window and the trailing edge oriented to point toward a central point of the optical system. A method of manufacturing a window baffle assembly is also provided.