A large field-of-view (FOV) imaging apparatus includes a monocentric lens, and a plurality of imaging modules comprising digital mirror device(s) (DMD) arranged to form or arranged in proximity to a spherical focal surface in optical communication with the monocentric lens such that the monocentric lens directs light rays that enter the monocentric lens at a surface of the monocentric lens towards the spherical focal surface and into the imaging modules as a function of incident angle of each light ray relative to a reference plane.

Various embodiments disclosed herein describe a divided-aperture infrared spectral imaging (DAISI) system that is adapted to acquire multiple IR images of a scene with a single-shot (also referred to as a snapshot). The plurality of acquired images having different wavelength compositions that are obtained generally simultaneously. The system includes at least two optical channels that are spatially and spectrally different from one another. Each of the at least two optical channels are configured to transfer IR radiation incident on the optical system towards an optical FPA unit comprising at least two detector arrays disposed in the focal plane of two corresponding focusing lenses. The system further comprises at least one temperature reference source or surface that is used to dynamically calibrate the two detector arrays and compensate for a temperature difference between the two detector arrays.

Various embodiments disclosed herein describe a divided-aperture infrared spectral imaging (DAISI) system that is adapted to acquire multiple IR images of a scene with a single-shot (also referred to as a snapshot). The plurality of acquired images having different wavelength compositions that are obtained generally simultaneously. The system includes at least two optical channels that are spatially and spectrally different from one another. Each of the at least two optical channels are configured to transfer IR radiation incident on the optical system towards an optical FPA unit comprising at least two detector arrays disposed in the focal plane of two corresponding focusing lenses. The system further comprises at least one temperature reference source or surface that is used to dynamically calibrate the two detector arrays and compensate for a temperature difference between the two detector arrays.

Various embodiments disclosed herein describe a divided-aperture infrared spectral imaging (DAISI) system that is adapted to acquire multiple IR images of a scene with a single-shot (also referred to as a snapshot). The plurality of acquired images having different wavelength compositions that are obtained generally simultaneously. The system includes at least two optical channels that are spatially and spectrally different from one another. Each of the at least two optical channels are configured to transfer IR radiation incident on the optical system towards an optical FPA unit comprising at least two detector arrays disposed in the focal plane of two corresponding focusing lenses. The system further comprises at least one temperature reference source or surface that is used to dynamically calibrate the two detector arrays and compensate for a temperature difference between the two detector arrays.

A light sensing circuit includes a photomultiplier in electrical communication with an array of capacitors or resistors. Each capacitor or resistor in the array having an associated switch and having a capacitance or resistance different from every other capacitor or resistor in the array. Each switch has an open state and a closed state, thus enabling each capacitor or resistor to be placed in electrical communication with the photomultiplier or be isolated from the photomultiplier. The switchable array may be in electrical communication with an analog to digital converter (ADC) or a transimpedance amplifier (TIA). The switchable array allows the ADC or TIA to be sensitive to low value signals and operate at a large dynamic range and operate at a fast rate.

Methods and apparatus to count people are disclosed. Example people counting apparatus disclosed herein include a difference calculator to calculate a degree of similarity between a first characteristic dataset and a second characteristic dataset representative of face detections in images. Disclosed example people counting apparatus also include a limiter to store the first characteristic dataset and the second characteristic dataset in a plurality of characteristic datasets associated when the degree of similarity does not satisfy a threshold, and to store the first characteristic dataset in the plurality of characteristic datasets and discard the second characteristic dataset when the degree of similarity satisfies the threshold to limit a number of stored characteristic datasets. Disclosed example people counting apparatus further include a comparator to compare the plurality of characteristic datasets to each other to determine a number of unique faces in an environment during a first period of time.

The invention concerns a method of image processing involving: receiving, by a processing device, an input image (IB) captured by a pixel array sensitive to infrared radiation; determining, based on the input image and on a column component vector (VCOL), a first scale factor (?) by estimating a level of the column spread present in the input image; generating column offset values (?.VCOL(y)) based on the product of the first scale factor with the values of the vector; determining, based on the input image and on a 2D dispersion matrix (IDISP), a second scale factor (?) by estimating a level of the 2D dispersion present in the input image; generating pixel offset values (?.IDISP(x,y)) based on the product of the second scale factor with the values of the matrix; and generating a corrected image (IC) by applying the column and pixel offset values.

The invention concerns a method of image processing involving: receiving, by a processing device, an input image (IB) captured by a pixel array sensitive to infrared radiation; determining, based on the input image and on a column component vector (VCOL), a first scale factor (?) by estimating a level of the column spread present in the input image; generating column offset values (?.VCOL(y)) based on the product of the first scale factor with the values of the vector; determining, based on the input image and on a 2D dispersion matrix (IDISP), a second scale factor (?) by estimating a level of the 2D dispersion present in the input image; generating pixel offset values (?.IDISP(x,y)) based on the product of the second scale factor with the values of the matrix; and generating a corrected image (IC) by applying the column and pixel offset values.

Methods and apparatus to count people are disclosed. An example apparatus includes a populator to populate a list with first characteristic datasets obtained from first image data representative of an environment during a first period of time, respective ones of the first characteristic datasets representative of a face detected in the environment during the first period of time; a comparator to compare the first characteristic datasets to each other to determine a first number of unique faces in the environment during the first period of time; and a discarder to delete the first characteristic datasets from the list when the first period of time has ended, the populator to re-populate the list with second characteristic datasets obtained from second image data representative of the environment during a second period of time subsequent to the first period of time.

Methods and apparatus to count people are disclosed. An example apparatus includes a populator to populate a list with first characteristic datasets obtained from first image data representative of an environment during a first period of time, respective ones of the first characteristic datasets representative of a face detected in the environment during the first period of time; a comparator to compare the first characteristic datasets to each other to determine a first number of unique faces in the environment during the first period of time; and a discarder to delete the first characteristic datasets from the list when the first period of time has ended, the populator to re-populate the list with second characteristic datasets obtained from second image data representative of the environment during a second period of time subsequent to the first period of time.