Abstract: Conventional methods for imaging transient targets are constrained by a trade-off between resolution and frame rate, and transient targets moving faster than the detector frame typically result in image blurring. Imagers using digital-pixel focal plane arrays (“DFPAs”) have on-chip global pixel operation capability for extracting a single transient-feature (i.e., single-frequency discrimination) in a snapshot that depends on the number of counters implemented per pixel. However, these DFPA systems are not capable of multi-target and multi-frequency discrimination. Imagers described herein achieve multi-target transient signature discrimination orders of magnitude faster than the readout frame rate using in-pixel electronic shuttering with a known time-encoded modulation. Three-dimensional (x,y,t) data cube reconstruction is performed using compressive sensing algorithms.

Abstract: Conventional methods for imaging transient targets are constrained by a trade-off between resolution and frame rate, and transient targets moving faster than the detector frame typically result in image blurring. Imagers using digital-pixel focal plane arrays (“DFPAs”) have on-chip global pixel operation capability for extracting a single transient-feature (i.e., single-frequency discrimination) in a snapshot that depends on the number of counters implemented per pixel. However, these DFPA systems are not capable of multi-target and multi-frequency discrimination. Imagers described herein achieve multi-target transient signature discrimination orders of magnitude faster than the readout frame rate using in-pixel electronic shuttering with a known time-encoded modulation. Three-dimensional (x,y,t) data cube reconstruction is performed using compressive sensing algorithms.

Abstract: Conventional methods for imaging transient targets are constrained by a trade-off between resolution and frame rate, and transient targets moving faster than the detector frame typically result in image blurring. Imagers using digital-pixel focal plane arrays (“DFPAs”) have on-chip global pixel operation capability for extracting a single transient-feature (i.e., single-frequency discrimination) in a snapshot that depends on the number of counters implemented per pixel. However, these DFPA systems are not capable of multi-target and multi-frequency discrimination. Imagers described herein achieve multi-target transient signature discrimination orders of magnitude faster than the readout frame rate using in-pixel electronic shuttering with a known time-encoded modulation. Three-dimensional (x,y,t) data cube reconstruction is performed using compressive sensing algorithms.

Abstract: Conventional methods for imaging transient targets are constrained by a trade-off between resolution and frame rate, and transient targets moving faster than the detector frame typically result in image blurring. Imagers using digital-pixel focal plane arrays (“DFPAs”) have on-chip global pixel operation capability for extracting a single transient-feature (i.e., single-frequency discrimination) in a snapshot that depends on the number of counters implemented per pixel. However, these DFPA systems are not capable of multi-target and multi-frequency discrimination. Imagers described herein achieve multi-target transient signature discrimination orders of magnitude faster than the readout frame rate using in-pixel electronic shuttering with a known time-encoded modulation. Three-dimensional (x,y,t) data cube reconstruction is performed using compressive sensing algorithms.

Abstract: Conventional methods for imaging transient targets are constrained by a trade-off between resolution and frame rate, and transient targets moving faster than the detector frame typically result in image blurring. Imagers using digital-pixel focal plane arrays (“DFPAs”) have on-chip global pixel operation capability for extracting a single transient-feature (i.e., single-frequency discrimination) in a snapshot that depends on the number of counters implemented per pixel. However, these DFPA systems are not capable of multi-target and multi-frequency discrimination. Imagers described herein achieve multi-target transient signature discrimination orders of magnitude faster than the readout frame rate using in-pixel electronic shuttering with a known time-encoded modulation. Three-dimensional (x,y,t) data cube reconstruction is performed using compressive sensing algorithms.

Abstract: Conventional methods for imaging transient targets are constrained by a trade-off between resolution and frame rate, and transient targets moving faster than the detector frame typically result in image blurring. Imagers using digital-pixel focal plane arrays (“DFPAs”) have on-chip global pixel operation capability for extracting a single transient-feature (i.e., single-frequency discrimination) in a snapshot that depends on the number of counters implemented per pixel. However, these DFPA systems are not capable of multi-target and multi-frequency discrimination. Imagers described herein achieve multi-target transient signature discrimination orders of magnitude faster than the readout frame rate using in-pixel electronic shuttering with a known time-encoded modulation. Three-dimensional (x,y,t) data cube reconstruction is performed using compressive sensing algorithms.

Abstract: Conventional methods for imaging transient targets are constrained by a trade-off between resolution and frame rate, and transient targets moving faster than the detector frame typically result in image blurring. Imagers using digital-pixel focal plane arrays (“DFPAs”) have on-chip global pixel operation capability for extracting a single transient-feature (i.e., single-frequency discrimination) in a snapshot that depends on the number of counters implemented per pixel. However, these DFPA systems are not capable of multi-target and multi-frequency discrimination. Imagers described herein achieve multi-target transient signature discrimination orders of magnitude faster than the readout frame rate using in-pixel electronic shuttering with a known time-encoded modulation. Three-dimensional (x,y,t) data cube reconstruction is performed using compressive sensing algorithms.

Abstract: Conventional methods for imaging transient targets are constrained by a trade-off between resolution and frame rate, and transient targets moving faster than the detector frame typically result in image blurring. Imagers using digital-pixel focal plane arrays (“DFPAs”) have on-chip global pixel operation capability for extracting a single transient-feature (i.e., single-frequency discrimination) in a snapshot that depends on the number of counters implemented per pixel. However, these DFPA systems are not capable of multi-target and multi-frequency discrimination. Imagers described herein achieve multi-target transient signature discrimination orders of magnitude faster than the readout frame rate using in-pixel electronic shuttering with a known time-encoded modulation. Three-dimensional (x,y,t) data cube reconstruction is performed using compressive sensing algorithms.

Abstract: Digital focal plane arrays (DFPAs) with multiple counters per unit cell can be used to convert analog signals to digital data and to filter the digital data. Exemplary DFPAs include two-dimensional arrays of unit cells, where each unit cell is coupled to a corresponding photodetector in a photodetector array. Each unit cell converts photocurrent from its photodetector to a digital pulse train that is coupled to multiple counters in the unit cell. Each counter in each unit cell can be independently controlled to filter the pulse train by counting up or down and/or by transferring data as desired. For example, a unit cell may perform in-phase/quadrature filtering of homodyne- or heterodyne-detected photocurrent with two counters: a first counter toggled between increment and decrement modes with an in-phase signal and a second counter toggled between increment and decrement modes with a quadrature signal.

Abstract: A method and a device useful for identifying or detecting the presence of a material of interest, such as an explosive or a biological contaminant, in a sample is presented herein. The sample is illuminated with electromagnetic radiation at a predetermined set of wavelengths. An example of an illumination source includes a quantum cascade laser (QCL). The radiation reflects from a sample and is detected at pixels of a detector. Examples of the detectors include digital focal plane array (DFPA) cameras. Intensity of the reflected radiation is measured at each illumination wavelength. The pixels can be configured to add weighted intensities of the reflected radiation, the weights of the intensities being based on a predicted optical response value for the sample at the wavelengths of the first set and the second set of wavelengths. Based on the sum of weighted intensities of the reflected radiation, the likelihood that the material is present within the sample is determined.