A method of imaging a target includes acquiring, by a processor of an imaging apparatus, multiple images of the target, wherein the multiple images have different exposure values; determining temporal and/or spatial variances for images with different exposure values; and generating a perfusion image of the target using results of the determining operation.

Systems and methods are provided for vehicle navigation. In one implementation, a navigation system for a host vehicle may comprise at least one processor. The processor may be programmed to receive from a first camera at least a first captured image representative of an environment of the host vehicle. The processor may be programmed to receive from a second camera at least a second captured image representative of the environment of the host vehicle. Both the first captured image and the second image includes a representation of the traffic light, and wherein the second camera is configured to operate in a primary mode where at least one operational parameter of the second camera is tuned to detect at least one feature of the traffic light. The processor may be further programmed cause at least one navigational action by the vehicle based on analysis of the representation of the traffic light.

In accordance with an embodiment, a computer-implemented method includes obtaining a time sequence of measurement frames of a radar measurement of a scene comprising an object; based on multiple subsequent measurement frames of the time sequence of measurement frames, determining one or more one-dimensional (1-D) time series of respective observables of the radar measurement associated with the object; and based on the one or more 1-D time series, determining a motion class of a motion performed by the object using a classification algorithm

An apparatus for detecting a specular surface in a scene is provided. The apparatus includes an illumination device configured to emit polarized light towards the scene. The apparatus further includes an imaging system configured to capture a first image of the scene based on light emanating from the scene. The light emanating from the scene includes one or more reflection of the emitted polarized light. The imaging system is further configured to capture a second image of the scene based on filtered light. The apparatus further includes a polarization filter configured to generate the filtered light by filtering the light emanating from the scene. The apparatus further includes processing circuitry configured to determine presence of the specular surface in the scene based on a comparison of the first image and the second image.

Technologies for thermal enhanced semantic segmentation include a computing device having a visible light camera and an infrared camera. The computing device receives a visible light image of a scene from the visible light camera and an infrared image of the scene from the infrared camera. The computing device registers the infrared image to the visible light image to generate a registered image. Registering the infrared image may include increasing resolution of the infrared image. The computing device generates a thermal boundary saliency image based on the registered infrared image. The computing device may generate the thermal boundary saliency image by applying a Gabor jet convolution to the registered infrared image. The computing device performs semantic segmentation on the visible light image, the registered infrared image, and the thermal boundary saliency image to generate a pixelwise semantic classification of the scene. Other embodiments are described and claimed.

Technologies for thermal enhanced semantic segmentation include a computing device having a visible light camera and an infrared camera. The computing device receives a visible light image of a scene from the visible light camera and an infrared image of the scene from the infrared camera. The computing device registers the infrared image to the visible light image to generate a registered image. Registering the infrared image may include increasing resolution of the infrared image. The computing device generates a thermal boundary saliency image based on the registered infrared image. The computing device may generate the thermal boundary saliency image by applying a Gabor jet convolution to the registered infrared image. The computing device performs semantic segmentation on the visible light image, the registered infrared image, and the thermal boundary saliency image to generate a pixelwise semantic classification of the scene. Other embodiments are described and claimed.

The present invention discloses a non-interferometric, non-iterative complex amplitude reading method and apparatus. The reading method includes the following steps: diffracting a light beam containing amplitude information and phase information to obtain a diffraction pattern with intensity variations; constructing a diffraction intensity-complex amplitude model and training it based on the correlation between the diffraction pattern and amplitude information and phase information, and applying the trained model directly to new diffraction images to obtain amplitude information and phase information. The method can achieve detection of complex amplitude information, including amplitude and phase, from a single diffraction image, improve the stability and accuracy of phase reading results, increase the calculation speed, and simplify the optical system. It is suitable for applications in holographic storage, biomedical image processing, and microscopic imaging, among others.

A projectile detection technique is disclosed. The technique helps improve the self-defense capabilities of strategic platforms such as naval ships against asymmetric threats such as anti-ship missiles (ASMs). These threats can be particularly challenging in a highly cluttered maritime environment, where the threats can be too close for radar to accurately detect. In one example, the projectile detection technique automatically detects ASMs flying above the horizon by using mid-wavelength infrared (MWIR) and visible/near-infrared (VNIR) camera systems, and locating the horizon line and segmenting the imagery into different regions. Projectiles are detected in the near-horizon segment using a Fourier phase-only transform and convolution matched filters to enhance exceedances, then applying multi-frame processing to measure persistence and scintillation (e.g., flicker from missile exhaust) to help filter out background clutter objects. The use of the phase-only transform, matched filters, and multi-frame processing helps detect single-point anomalies and distinguish ASMs from background clutter.

Disclosed herein are methods and systems for object recognition utilizing reflective light blocking. Further disclosed herein are systems and methods for recognition of at least one fluorescent object being present in a scene by using a light source including at least one illuminant and a bandpass filter for each illuminant of the light source, a sensor array including at least one light sensitive sensor and at least one filter selectively blocking the reflected light originating from illuminating the scene with the light source and allowing passage of luminescence originating from illuminating the scene with the light source into the at least one color sensitive sensor, and a processing unit for identifying the at least one object based on the data detected by the sensory array and known data on luminescence properties associated with known objects.

A method includes identifying one or more codewords of a bit sequence that fail to satisfy at least one codeword constraint. The method also includes removing the one or more codewords from the bit sequence to generate a punctured bit sequence. The method further includes determining whether the punctured bit sequence is symmetric. The method includes, in response to determining that the punctured bit sequence is symmetric, generating a hermitian symmetric codebook primitive based at least in part on the punctured bit sequence, where the hermitian symmetric codebook primitive is useable to form a diffractive optical element (DOE) of a structured light depth sensing system.