Abstract: Discussed herein are systems, devices, and methods for filtering digital elevation map (DEM) data. A method can include ingesting digital elevation map (DEM) data and intensity data from a panchromatic (PAN) or multi-spectral (MS) image, filling in voids in the ingested DEM data using local interpolation to create interpolated DEM data, creating a shadow map based on the received intensity data, modifying, using the created shadow map, a height of one or more pixels in the interpolated DEM data to create a modified DEM file, and storing the modified DEM file in a memory.

Abstract: Embodiments of a method and apparatus for video enhancement are generally described herein. In some embodiments, the method includes accessing a first frame of the video. The first frame can include pixel data with intensity values within one of a number of non-overlapping ranges of intensity values. The method can further include compressing the intensity values of the first pixel data to generate non-linearly compressed (NLC) pixel data such that the intensity values are compressed into smaller ranges of intensity values. The method can further include upsampling the NLC pixel data based on an upsampling ratio. The method can further include decompressing the intensity values of the upsampled pixel data by reassigning intensity values of the upsampled pixel data to intensity values in the original intensity value ranges. Other example methods, systems, and apparatuses are described.

Abstract: Discussed herein are systems, devices, and methods for filtering digital elevation map (DEM) data. A method can include ingesting digital elevation map (DEM) data and intensity data from a panchromatic (PAN) or multi-spectral (MS) image, filling in voids in the ingested DEM data using local interpolation to create interpolated DEM data, creating a shadow map based on the received intensity data, modifying, using the created shadow map, a height of one or more pixels in the interpolated DEM data to create a modified DEM file, and storing the modified DEM file in a memory.

Abstract: Generally discussed herein are systems and apparatuses that relate to systems and methods for analysis of 3D light radar (LiDAR) point clouds. The disclosure also includes techniques of bare earth and feature extraction. According to an example, bare earth and feature extraction can include estimation of a ground layer, generation of an inverse Above Ground Layer (AGL), identification of paths, roads, and cleared areas, identification and removal of buildings, and identification of a Human Activity Layer (HAL). This combination of features may provide for a much higher probability of detection of human activity.

Abstract: Generally discussed herein are systems and apparatuses that relate to systems and methods for analysis of 3D light radar (LiDAR) point clouds. The disclosure also includes techniques of bare earth and feature extraction. According to an example, bare earth and feature extraction can include estimation of a ground layer, generation of an inverse Above Ground Layer (AGL), identification of paths, roads, and cleared areas, identification and removal of buildings, and identification of a Human Activity Layer (HAL). This combination of features may provide for a much higher probability of detection of human activity.

Abstract: Embodiments of a method and apparatus for image enhancement are generally described herein. In some embodiments, the method includes accessing two or more sets of first pixel data representative of two or more images of a physical object. The method can further include transforming the two or more sets of pixel data to generate two or more sets of frequency domain data. The method can further include upsampling each of the two or more sets of frequency domain data to generate a set of upsampled frequency domain data. The method can further include re-transforming the set of upsampled frequency domain data to generate two or more sets of second pixel data. The method can further include combining two or more sets of second pixel data to generate an enhanced image of the physical object. Other example methods, systems, and apparatuses are described.

Abstract: A method includes receiving image data obtained by a laser imaging system. The method also includes identifying a minimum post spacing obtainable in a three-dimensional image constructed using the image data. The minimum post spacing defines a maximum obtainable resolution of the image. Identifying the minimum post spacing includes using (i) multiple point spread functions associated with the image data and (ii) a number of laser pulses directed at a specified area by the imaging system during capture of the image data. Identifying the minimum post spacing may also include using (iii) a minimum contrast ratio associated with the image. The point spread functions may be associated with different point reflectors, have a Gaussian distribution, and overlap.

Abstract: An apparatus and method for image processing of XYZ point clouds obtained from a GmAPD LADAR using low-pass filtering followed by high-pass filtering and deconvolution. Preferably, the low-pass filter parameters are developed numerically utilizing Weiner-Levinson Deconvolution (WLD).

Abstract: A method, in accordance with particular embodiments, includes receiving voxel data for a plurality of voxels. Each voxel is associated with a unique volume of space associated with a geographic area. The voxel data for each respective voxel includes one or more values based on one or more reflections from one or more light pulses from a LIDAR system. The method further includes identifying noise values from among the one or more values for each respective voxel. The method additionally includes determining a baseline threshold comprising a static value that is uniform for each of the voxels. The method additionally includes determining a dynamic threshold that varies between the voxels and is based on the identified noise values. The method further includes applying the baseline and dynamic thresholds to the voxel data to generate filtered voxel data. The method also includes generating a three-dimensional image based on the filtered voxel data.

Abstract: A method for processing XYZ point cloud of a scene acquired by a GmAPD LADAR includes: performing on a computing device a three-dimensional statistical differencing on the XYZ point cloud obtained from the GmAPD LADAR to produce a SD point cloud; and displaying an image of the SD point cloud.

Abstract: A method includes obtaining image data associated with a specified area having one or more objects. The method also includes segmenting the image data into one or more segments associated with the one or more objects. The method further includes analyzing each of the one or more segments to identify a vibrometry spectrum associated with the corresponding object. In addition, the method includes generating an image of the specified area using the vibrometry spectrum associated with each object. The image of the specified area could illustrate each of the one or more objects with an intensity based on a total power of that target's total vibrational energy. The image of the specified area could also illustrate movement of at least one object over time.

Abstract: In one aspect, a computerized method to automatically detect buildings includes determining if each point of a set of filtered points is on a line by processing the set of filtered points in one pass including a) locating a first point of the set of filter points nearest to a second point of the set of filtered points, b) determining if the distance between the first point and the second point is greater than a distance threshold; c) determining if the first point and the second point have collinearity greater than a collinearity threshold; and d) designating the first point as an endpoint of a line that includes the second point if the distance between the first point and the second point is greater than the distance threshold and if the first point and the second point have collinearity greater than the collinearity threshold.

Abstract: A method includes obtaining image data associated with a specified area having one or more objects. The method also includes segmenting the image data into one or more segments associated with the one or more objects. The method further includes analyzing each of the one or more segments to identify a vibrometry spectrum associated with the corresponding object. In addition, the method includes generating an image of the specified area using the vibrometry spectrum associated with each object. The image of the specified area could illustrate each of the one or more objects with an intensity based on a total power of that target's total vibrational energy. The image of the specified area could also illustrate movement of at least one object over time.

Abstract: In one aspect, a computerized method to automatically determine thresholds includes receiving data generated from a Geiger-mode avalanche photodiode (GmAPD) laser detecting and ranging (LADAR) sensor of a scene, determining an overall threshold value for the scene using a binomial distribution and determining post threshold values for each x-y position in the scene. The computerized method also includes, for each x-y position, using a maximum value of the post threshold values and the overall threshold value to filter the data from the scene.

Abstract: A method includes receiving image data obtained by a laser imaging system. The method also includes identifying a minimum post spacing obtainable in a three-dimensional image constructed using the image data. The minimum post spacing defines a maximum obtainable resolution of the image. Identifying the minimum post spacing includes using (i) multiple point spread functions associated with the image data and (ii) a number of laser pulses directed at a specified area by the imaging system during capture of the image data. Identifying the minimum post spacing may also include using (iii) a minimum contrast ratio associated with the image. The point spread functions may be associated with different point reflectors, have a Gaussian distribution, and overlap.

Abstract: In one aspect, a computerized method to automatically detect buildings includes determining if each point of a set of filtered points is on a line by processing the set of filtered points in one pass including a) locating a first point of the set of filter points nearest to a second point of the set of filtered points, b) determining if the distance between the first point and the second point is greater than a distance threshold; c) determining if the first point and the second point have collinearity greater than a collinearity threshold; and d) designating the first point as an endpoint of a line that includes the second point if the distance between the first point and the second point is greater than the distance threshold and if the first point and the second point have collinearity greater than the collinearity threshold.

Abstract: A method, in accordance with particular embodiments, includes receiving voxel data for a plurality of voxels. Each voxel is associated with a unique volume of space associated with a geographic area. The voxel data for each respective voxel includes one or more values based on one or more reflections from one or more light pulses from a LIDAR system. The method further includes identifying noise values from among the one or more values for each respective voxel. The method additionally includes determining a baseline threshold comprising a static value that is uniform for each of the voxels. The method additionally includes determining a dynamic threshold that varies between the voxels and is based on the identified noise values. The method further includes applying the baseline and dynamic thresholds to the voxel data to generate filtered voxel data. The method also includes generating a three-dimensional image based on the filtered voxel data.

Abstract: A method for processing XYZ point cloud of a scene acquired by a GmAPD LADAR includes: performing on a computing device a three-dimensional statistical differencing on the XYZ point cloud obtained from the GmAPD LADAR to produce a SD point cloud; and displaying an image of the SD point cloud.

Abstract: An apparatus and method for processing of XYZ point clouds obtained from a GmAPD LADAR using low-pass filtering followed by high-pass filtering and deconvolution.

Abstract: A System and Method for CW interference suppression in pulsed signal processing having a front-end, an A/D converter, a data store, and a suppressor module coupled to both the A/D converter and the data store. The front-end is operable to receive a waveform and communicate such to the A/D converter to digitize for processing by the suppressor module. The suppressor module being operable to further process the digitized waveform by way of applying a FFT to obtain a corresponding amplitude spectrum of the digitized waveform, clipping the amplitude spectrum to obtain a clipped amplitude spectrum, performing successive piece-wise IFFTs on the positive frequency points of the clipped amplitude spectrum to obtain multiple amplitude-time series, each having a frequency value assigned, and then stacking such amplitude-time series successively in the data store to form a time-frequency spectrogram array to thereby facilitate suppression of interference signals and detection of data pulses.