Abstract: Image sensor modules include primary high-resolution imagers and secondary imagers. For example, an image sensor module may include a semiconductor chip including photosensitive regions defining, respectively, a primary camera and a secondary camera. The image sensor module may include an optical assembly that does not substantially obstruct the field-of-view of the secondary camera. Some modules include multiple secondary cameras that have a field-of-view at least as large as the field-of-view of the primary camera. Various features are described to facilitate acquisition of signals that can be used to calculate depth information.

Abstract: Image sensor modules include primary high-resolution imagers and secondary imagers. For example, an image sensor module may include a semiconductor chip including photosensitive regions defining, respectively, a primary camera and a secondary camera. The image sensor module may include an optical assembly that does not substantially obstruct the field-of-view of the secondary camera. Some modules include multiple secondary cameras that have a field-of-view at least as large as the field-of-view of the primary camera. Various features are described to facilitate acquisition of signals that can be used to calculate depth information.

Abstract: Image sensor modules include primary high-resolution imagers and secondary imagers. For example, an image sensor module may include a semiconductor chip including photosensitive regions defining, respectively, a primary camera and a secondary camera. The image sensor module may include an optical assembly that does not substantially obstruct the field-of-view of the secondary camera. Some modules include multiple secondary cameras that have a field-of-view at least as large as the field-of-view of the primary camera. Various features are described to facilitate acquisition of signals that can be used to calculate depth information.

Abstract: Techniques are described for generating a distance map (e.g., a map of disparity, depth or other distance values) for image elements (e.g., pixels) of an image capture device. The distance map is generated based on an initial distance map (obtained, e.g., using a block or code matching algorithm) and a segmentation map (obtained using a segmentation algorithm). In some instances, the resulting distance map can be less sparse than the initial distance map, can contain more accurate distance values, and can be sufficiently fast for real-time or near real-time applications. The resulting distance map can be converted, for example, to a color-coded distance map of a scene that is presented on a display device.

Abstract: An apparatus for producing structured light comprises a first optical arrangement which comprises a microlens array (L1) comprising a multitude of transmissive or reflective microlenses (2) which are regularly arranged at a lens pitch P and an illumination unit for illuminating the microlens array. The illumination unit comprises an array (S1) of light sources (1) for emitting light of a wavelength L each and having an aperture each, wherein the apertures are located in a common emission plane which is located at a distance D from the microlens array. For the lens pitch P, the distance D and the wavelength L, the following equation applies P2=2LD/N, wherein N is an integer with N?1. High-contrast high-intensity light patterns can be produced. Devices comprising such apparatuses can be used for depth mapping.

Abstract: A brightness image of a scene is converted into a corresponding frequency domain image and it is determined whether a threshold condition is satisfied for each of one or more regions of interest in the frequency domain image, the threshold condition being that the number of frequencies in the region of interest is at least as high as a threshold value. The results of the determination can be used to facilitate selection of an appropriate block matching algorithm for deriving disparity or other distance data and/or to control adjustment of an illumination source that generates structured light for the scene.

Abstract: The present disclosure describes structured-stereo imaging assemblies including separate imagers for different wavelengths. The imaging assembly can include, for example, multiple imager sub-arrays, each of which includes a first imager to sense light of a first wavelength or range of wavelengths and a second imager to sense light of a different second wavelength or range of wavelengths. Images acquired from the imagers can be processed to obtain depth information and/or improved accuracy. Various techniques are described that can facilitate determining whether any of the imagers or sub-arrays are misaligned.

Abstract: A brightness image of a scene is converted into a corresponding frequency domain image and it is determined whether a threshold condition is satisfied for each of one or more regions of interest in the frequency domain image, the threshold condition being that the number of frequencies in the region of interest is at least as high as a threshold value. The results of the determination can be used to facilitate selection of an appropriate block matching algorithm for deriving disparity or other distance data and/or to control adjustment of an illumination source that generates structured light for the scene.

Abstract: An apparatus for producing structured light comprises a first optical arrangement which comprises a microlens array (L1) comprising a multitude of transmissive or reflective microlenses (2) which are regularly arranged at a lens pitch P and an illumination unit for illuminating the microlens array. The illumination unit comprises an array (S1) of light sources (1) for emitting light of a wavelength L each and having an aperture each, wherein the apertures are located in a common emission plane which is located at a distance D from the microlens array. For the lens pitch P, the distance D and the wavelength L, the following equation applies P2=2LD/N, wherein N is an integer with N?1. High-contrast high-intensity light patterns can be produced. Devices comprising such apparatuses can be used for depth mapping.

Abstract: Providing a disparity map includes acquiring first and second stereo images, binarizing the first stereo image to obtain a binarized image, and applying a block matching technique to the first and second stereo images to obtain an initial disparity map in which individual image elements are assigned a respective initial disparity value. For each respective image element, an updated disparity value that represents a product of the initial disparity value assigned to the image element and a value associated with the image element in the binarized image is obtained. An updated disparity map can be generated and represents the updated disparity values of the image elements.

Abstract: Techniques are described for generating a distance map (e.g., a map of disparity, depth or other distance values) for image elements (e.g., pixels) of an image capture device. The distance map is generated based on an initial distance map (obtained, e.g., using a block or code matching algorithm) and a segmentation map (obtained using a segmentation algorithm). In some instances, the resulting distance map can be less sparse than the initial distance map, can contain more accurate distance values, and can be sufficiently fast for real-time or near real-time applications. The resulting distance map can be converted, for example, to a color-coded distance map of a scene that is presented on a display device.

Abstract: Image sensor modules include primary high-resolution imagers and secondary imagers. For example, an image sensor module may include a semiconductor chip including photosensitive regions defining, respectively, a primary camera and a secondary camera. The image sensor module may include an optical assembly that does not substantially obstruct the field-of-view of the secondary camera. Some modules include multiple secondary cameras that have a field-of-view at least as large as the field-of-view of the primary camera. Various features are described to facilitate acquisition of signals that can be used to calculate depth information.

Abstract: The present disclosure describes structured-stereo imaging assemblies including separate imagers for different wavelengths. The imaging assembly can include, for example, multiple imager sub-arrays, each of which includes a first imager to sense light of a first wavelength or range of wavelengths and a second imager to sense light of a different second wavelength or range of wavelengths. Images acquired from the imagers can be processed to obtain depth information and/or improved accuracy. Various techniques are described that can facilitate determining whether any of the imagers or sub-arrays are misaligned.

Abstract: An apparatus for producing structured light comprises a first optical arrangement which comprises a microlens array comprising a multitude of transmissive or reflective microlenses which are regularly arranged at a lens pitch P and an illumination unit for illuminating the microlens array. The illumination unit comprises an array of light sources for emitting light of a wavelength L each and having an aperture each, wherein the apertures are located in a common emission plane which is located at a distance D from the microlens array. For the lens pitch P, the distance D and the wavelength L, the following equation applies P2=2LD/N, wherein N is an integer with N?1. High-contrast high-intensity light patterns can be produced.

Abstract: A method for performing column/row pattern suppression in a digital input image includes creating a smoothed version of the input image by averaging a set of columns/rows neighboring around the column/row being corrected. A difference image is constructed by subtracting the smoothed image from the input image. New column/row intensities are computed from the difference image. An output image is constructed with suppressed column/row patterns by subtracting the new column/row intensities from the input image.

Abstract: A method for performing column/row pattern suppression in a digital input image includes creating a smoothed version of the input image by averaging a set of columns/rows neighboring around the column/row being corrected. A difference image is constructed by subtracting the smoothed image from the input image. New column/row intensities are computed from the difference image. An output image is constructed with suppressed column/row patterns by subtracting the new column/row intensities from the input image.

Abstract: A method for performing column/row pattern suppression in a digital input image includes creating a smoothed version of the input image by averaging a set of columns/rows neighboring around the column/row being corrected. A difference image is constructed by subtracting the smoothed image from the input image. New column/row intensities are computed from the difference image. An output image is constructed with suppressed column/row patterns by subtracting the new column/row intensities from the input image.

Abstract: A method for performing column/row pattern suppression in a digital input image includes creating a smoothed version of the input image by averaging a set of columns/rows neighboring around the column/row being corrected. A difference image is constructed by subtracting the smoothed image from the input image. New column/row intensities are computed from the difference image. An output image is constructed with suppressed column/row patterns by subtracting the new column/row intensities from the input image.