Abstract: Imposing a priori knowledge to estimate turbulence. The method includes receiving, at a memory, an original input image from an imaging instrument having an imaging wavelength and an optical aperture; and receiving, via a user input device and a graphical user interface, input of two or more points configured to substantially represent at least one feature. A processor estimates an atmospheric correlation length based on the received input of the two or more points, the imaging wavelength, and a size of the optical aperture. The processor mitigates turbulence in the original input image; and calculates a strength of the at least one feature based on the received input of the two or more points; until the atmospheric correlation length is optimal. If the atmospheric correlation length is not optimal, repeating the mitigation and calculation steps. The method also includes generating a turbulence-mitigated image based on the optimal atmospheric correlation length.

Abstract: Imposing a priori knowledge to estimate turbulence. The method includes receiving, at a memory, an original input image from an imaging instrument having an imaging wavelength and an optical aperture; and receiving, via a user input device and a graphical user interface, input of two or more points configured to substantially represent at least one feature. A processor estimates an atmospheric correlation length based on the received input of the two or more points, the imaging wavelength, and a size of the optical aperture. The processor mitigates turbulence in the original input image; and calculates a strength of the at least one feature based on the received input of the two or more points; until the atmospheric correlation length is optimal. If the atmospheric correlation length is not optimal, repeating the mitigation and calculation steps. The method also includes generating a turbulence-mitigated image based on the optimal atmospheric correlation length.

Abstract: A shadow brightening method includes receiving, at a memory device, an original input image, a brightening level, and a threshold pixel intensity. If a pixel intensity is greater than the threshold, then the pixel is considered bright. Otherwise, the pixel is shadowed. The method includes calculating a gamma transformation for each pixel. If the pixel intensity is less than or equal to the threshold, then a gamma transformation equal to the received brightening level is applied. If the pixel intensity is greater than the threshold, then the gamma transformation is scaled to decrease with intensity. For each shadowed pixel, the method includes computing a minimum value. It also includes determining the brightening level to be applied, thus creating a gamma map. The method also includes applying the determined brightening level to the shadowed pixels and outputting a shadow-brightened output image.

Abstract: A shadow brightening method includes receiving, at a memory device, an original input image, a brightening level, and a threshold pixel intensity. If a pixel intensity is greater than the threshold, then the pixel is considered bright. Otherwise, the pixel is shadowed. The method includes calculating a gamma transformation for each pixel. If the pixel intensity is less than or equal to the threshold, then a gamma transformation equal to the received brightening level is applied. If the pixel intensity is greater than the threshold, then the gamma transformation is scaled to decrease with intensity. For each shadowed pixel, the method includes computing a minimum value. It also includes determining the brightening level to be applied, thus creating a gamma map. The method also includes applying the determined brightening level to the shadowed pixels and outputting a shadow-brightened output image.

Abstract: A method for mitigating turbulence in an image. A set of initial turbulence parameters is chosen. A fast de-turbulence algorithm is applied using each initial turbulence parameter to an original image, resulting in an enhanced image. The sharpness of each enhanced image is measured. The sharpness is recorded along with the corresponding initial turbulence parameter in a sharpness curve. The knee of the sharpness curve is calculated. An estimated turbulence parameter r0 is determined according to the knee. A de-turbulence algorithm is applied to the original image using r0.

Abstract: A memory device receives an original input image having at least one horizontal reticle or at least one vertical reticle. The memory device also receives a horizontal reticle mask image for horizontal reticles and/or a vertical reticle mask image for vertical reticles. A processor inpaints three regions: (1) vertical reticles with a horizontal filter, (2) horizontal reticles with a vertical filter, and (3) an intersection of the horizontal and vertical reticles with a two dimensional filter. A single inpainted image is produced. The processor determines whether a maximum change in any one of the first inpainted region, the second inpainted region or the third inpainted region equals or exceeds a predetermined threshold, and if so, repeating the inpainting steps. Once the maximum change in pixel intensity is less than the predetermined threshold the processing stops.

Abstract: An in-phase quadrature (IQ) modulator modulates a radio frequency signal to produce an IQ-modulated radio frequency signal. A polarization modulator modulates the IQ modulated radio frequency signal to produce a polarization-modulated radio frequency signal. The polarization modulator outputs the polarization-modulated radio frequency signal to an antenna for transmission.

Abstract: A method of providing accurate position, navigation, and timing information comprising the steps of providing at least four transceiver devices, providing an auxiliary GPS device, and providing a receiver GPS device. Each transceiver devices receives a plurality of GPS signals from a plurality of GPS satellites, and calculates a transceiver position and transceiver velocity vector. The transceiver position, transceiver velocity vector, and GPS signal are repackaged at each transceiver into a first spread signal structure, which is transmitted from each transceiver as a first GPS-like signal. The GPS-like signal is received at an auxiliary GPS device, which generates a simulated GPS signal. This simulated GPS signal is then output and received by a simulated GPS device.

Abstract: A method and system for bidirectional edge highlighting. A memory receives an original input image. A processor calculates edge intensity for each edge pixel in the original input image. The processor also identifies strong edges and attenuates said strong edges. The processor can further determine whether the attenuated strong edges should be bright or dark based on the intensity of the pixel in the original image. The processor applies bidirectional edge highlighting to the image based on the intensity of the pixel in the original image. The degree of darkness or brightness of the highlighting is based on the calculated edge intensity after strong edge attenuation.

Abstract: A method and system for bidirectional edge highlighting. A memory receives an original input image. A processor calculates edge intensity for each edge pixel in the original input image. The processor also identifies strong edges and attenuates said strong edges. The processor can further determine whether the attenuated strong edges should be bright or dark based on the intensity of the pixel in the original image. The processor applies bidirectional edge highlighting to the image based on the intensity of the pixel in the original image. The degree of darkness or brightness of the highlighting is based on the calculated edge intensity after strong edge attenuation.

Abstract: A method for mitigating turbulence in an image. A set of initial turbulence parameters is chosen. A fast de-turbulence algorithm is applied using each initial turbulence parameter to an original image, resulting in an enhanced image. The sharpness of each enhanced image is measured. The sharpness is recorded along with the corresponding initial turbulence parameter in a sharpness curve. The knee of the sharpness curve is calculated. An estimated turbulence parameter r0 is determined according to the knee. A de-turbulence algorithm is applied to the original image using r0.

Abstract: A transmitter includes: a data providing component that provides data to be transmitted; a transforming component that generates transformed data based on the data to be transmitted; and a transmitting component that transmits the transformed data. The transforming component includes a modulator, a code generator and a data structure having stored therein a first mathematical function. The first mathematical function includes a primary first function term. The primary first function term includes a first parameter within a predetermined first delineated boundary of parameters. The code generator generates coded data so as to form an error-detecting code from the data to be transmitted. The modulator modulates the coded data with the primary first function term.

Abstract: A method of providing accurate position, navigation, and timing information comprising the steps of providing at least four transceiver devices, providing an auxiliary GPS device, and providing a receiver GPS device. Each transceiver devices receives a plurality of GPS signals from a plurality of GPS satellites, and calculates a transceiver position and transceiver velocity vector. The transceiver position, transceiver velocity vector, and GPS signal are repackaged at each transceiver into a first spread signal structure, which is transmitted from each transceiver as a first GPS-like signal. The GPS-like signal is received at an auxiliary GPS device, which generates a simulated GPS signal. This simulated GPS signal is then output and received by a simulated GPS device.

Abstract: A system and method for haze removal. The method comprises the steps of receiving, at a memory, an input image having pixels. The method further comprises converting, by a processor, each pixel in each channel of the input image to floating-point values in the range of zero to one [0,1], and brightness-correcting, by the processor, the input image to prevent the de-hazed output image from becoming overly dark. The method also includes estimating, by the processor, the airlight for the brightness-corrected image, calculating a transmission map for each color or intensity channel of the image, and refining the transmission map for each said color or intensity. A reduced-haze image is thereby provided.

Abstract: Methods for characterizing radar can include the steps of receiving a plurality of radar emissions, and determining a plurality of Pulse Repetition Intervals (PRIs) corresponding to the emissions. A plurality of clocks Xi can be calculated using the PRIs. A clock range and a clock interval can be defined for the plurality of calculated clocks Xi and a clock X can be estimated, but only for the clocks Xi that are within the defined clock range. Countdowns Ci can be determined using the calculated clock X, and a mode M and crystal b can be calculated based on Ci. Clock X, countdowns Ci, mode M and crystal b, when considered together can accurately characterize a specific radar emission (and radar the emission came from). The systems and methods can be accomplished using emissions that are being received in real time using a receiver and emissions data from a database simultaneously.

Abstract: A method and system for automatically adjusting an iris opening in an imaging system. The method includes an iterative process that continues to adjust the camera's iris opening until an algorithm stopping condition is met. More particularly, a processor determines a brightness for the image at the current aperture setting. The processor classifies the image according to one of at least two brightness regime classifications. Based on the classifying step, the processor selects a pre-set optimal brightness parameter. The processor compares the brightness value of the image to the pre-set optimal value. The camera's iris opening is automatically adjusted based on a formula that takes into account, the current f-stop setting, the current brightness value, and the optimal brightness value. The iterative process continues until an algorithm stopping condition is met.

Abstract: A system and method for haze removal. The method comprises the steps of receiving, at a memory, an input image having pixels. The method further comprises converting, by a processor, each pixel in each channel of the input image to floating-point values in the range of zero to one [0,1], and brightness-correcting, by the processor, the input image to prevent the de-hazed output image from becoming overly dark. The method also includes estimating, by the processor, the airlight for the brightness-corrected image, calculating a transmission map for each color or intensity channel of the image, and refining the transmission map for each said color or intensity. A reduced-haze image is thereby provided.

Abstract: A transmitter includes: a data providing component that provides data to be transmitted; a transforming component that generates transformed data based on the data to be transmitted; and a transmitting component that transmits the transformed data. The transforming component includes a modulator, a code generator and a data structure having stored therein a first mathematical function. The first mathematical function includes a primary first function term. The primary first function term includes a first parameter within a predetermined first delineated boundary of parameters. The code generator generates coded data so as to form an error-detecting code from the data to be transmitted. The modulator modulates the coded data with the primary first function term.

Abstract: A method and system for automatically adjusting an iris opening in an imaging system. The method includes an iterative process that continues to adjust the camera's iris opening until an algorithm stopping condition is met. More particularly, a processor determines a brightness for the image at the current aperture setting. The processor classifies the image according to one of at least two brightness regime classifications. Based on the classifying step, the processor selects a pre-set optimal brightness parameter. The processor compares the brightness value of the image to the pre-set optimal value. The camera's iris opening is automatically adjusted based on a formula that takes into account, the current f-stop setting, the current brightness value, and the optimal brightness value. The iterative process continues until an algorithm stopping condition is met.

Abstract: A method involves receiving at least one analog signal from a transmitter, converting the analog signal to digital waveform data representing the analog signal and storing the digital waveform data in a first memory storage area. The digital waveform data includes cyclic redundancy check (CRC) error-checking code and informational message data, and is modulated by an unknown frequency rate parameter. A chirp adjustment function is performed that includes multiplying the digital waveform data by a non-linear data array to correct for the unknown frequency rate parameter. An error-checking function is performed using the CRC error-checking code. If an error is found, the method involves iteratively performing the chirp adjustment function and the error-checking function. The method may be implemented in a receiver in a mobile communications system to correct for acceleration effects of the receiver.