Abstract: Aspects of the present disclosure relate to systems and methods for determining a resampler for resampling or converting non-Bayer patter color filter array image data to Bayer pattern image data. An example device may include a camera having an image sensor with a non-Bayer pattern color filter array configured to capture non-Bayer pattern image data for an image. The example device also may include a memory and a processor coupled to the memory. The processor may be configured to receive the non-Bayer pattern image data from the image sensor, divide the non-Bayer pattern image data into portions, determine a sampling filter corresponding to the portions, and determine, based on the determined sampling filter, a resampler for converting non-Bayer pattern image data to Bayer-pattern image data.

Abstract: Systems and methods for reconstructing an object boundary in a disparity map generated by a structured light system are disclosed. One aspect is a structured light system. The system includes an image projecting device configured to project codewords. The system further includes a receiver device including a sensor, the receiver device configured to sense the projected codewords reflected from an object. The system further includes a processing circuit configured to generate a disparity map of the object, detect a first boundary of the object in the disparity map, identify a shadow region in the disparity map adjoining the first boundary, the shadow region including pixels with codeword outages, and change a shape of the object in the disparity map based on the detected shadow region. The system further includes a memory device configured to store the disparity map.

Abstract: Exemplary embodiments are directed to configurable demodulation of image data produced by an image sensor. In some aspects, a method includes receiving information indicating a configuration of the image sensor. In some aspects, the information may indicate a configuration of sensor elements and/or corresponding color filters for the sensor elements. A modulation function may then be generated based on the information. In some aspects, the method also includes demodulating the image data based on the generated modulation function to determine chrominance and luminance components of the image data, and generating the second image based on the determined chrominance and luminance components.

Abstract: Aspects of the present disclosure relate to systems and methods for determining a resampler for resampling or converting non-Bayer patter color filter array image data to Bayer pattern image data. An example device may include a camera having an image sensor with a non-Bayer pattern color filter array configured to capture non-Bayer pattern image data for an image. The example device also may include a memory and a processor coupled to the memory. The processor may be configured to receive the non-Bayer pattern image data from the image sensor, divide the non-Bayer pattern image data into portions, determine a sampling filter corresponding to the portions, and determine, based on the determined sampling filter, a resampler for converting non-Bayer pattern image data to Bayer-pattern image data.

Abstract: An electronic device for selecting a transform is described. The electronic device includes at least one image sensor, a memory, and a processor coupled to the memory and to the at least one image sensor. The processor is configured to obtain at least two images from the at least one image sensor. The processor is also configured to characterize structural content of each of the at least two images to produce a characterization for each image that is relevant to transform performance. The processor is further configured to select at least one transform from a set of transforms based on the characterization. The processor is additionally configured to apply the at least one transform to at least one of the images to substantially align the at least two images.

Abstract: Aspects relate to a method of generating a high-resolution image containing depth information of an object. In one aspect, the method includes downsampling a first reference image and a second reference image from a first resolution to a second resolution, wherein the first resolution is higher than the second resolution, and wherein the first reference image and the second reference image comprising a stereo image pair. The method further includes generating a depth map at the second resolution based on global minimization techniques, using the downsampled stereo image pair. The method also includes upsampling the depth map from the second resolution to the first resolution and using a guided filter to align contours of the upsampled depth map to contours of the first reference image.

Abstract: Certain aspects relate to systems and techniques for performing local intensity equalization on images in a set of images exhibiting local intensity variations. For example, the local intensity equalization can be used to perform accurate region matching and alignment of the images. The images can be partitioned into regions of pixel blocks, for instance based on location, shape, and size of identified keypoints in the images. Regions depicting the same feature in the images can be equalized with respect to intensity. Region matching based on the keypoints in the intensity-equalized regions can be performed with accuracy even in images captured by asymmetric sensors or exhibiting spatially varying intensity.

Abstract: An interactive display, including a cover glass having a front surface that includes a viewing area provides an input/output (I/O) interface for a user of an electronic device. An arrangement includes a processor, a light source, and a camera disposed outside the periphery of the viewing area coplanar with or behind the cover glass. The camera receives scattered light resulting from interaction, with an object, of light outputted from the interactive display, the outputted light being received by the cover glass from the object and directed toward the camera. The processor determines, from image data output by the camera, an azimuthal angle of the object with respect to an optical axis of the camera and/or a distance of the object from the camera.

Abstract: Systems and methods for reconstructing an object boundary in a disparity map generated by a structured light system are disclosed. One aspect is a structured light system. The system includes an image projecting device configured to project codewords. The system further includes a receiver device including a sensor, the receiver device configured to sense the projected codewords reflected from an object. The system further includes a processing circuit configured to generate a disparity map of the object, detect a first boundary of the object in the disparity map, identify a shadow region in the disparity map adjoining the first boundary, the shadow region including pixels with codeword outages, and change a shape of the object in the disparity map based on the detected shadow region. The system further includes a memory device configured to store the disparity map.

Abstract: Exemplary embodiments are directed to configurable demodulation of image data produced by an image sensor. In some aspects, a method includes receiving information indicating a configuration of the image sensor. In some aspects, the information may indicate a configuration of sensor elements and/or corresponding color filters for the sensor elements. A modulation function may then be generated based on the information. In some aspects, the method also includes demodulating the image data based on the generated modulation function to determine chrominance and luminance components of the image data, and generating the second image based on the determined chrominance and luminance components.

Abstract: Exemplary embodiments are directed to configurable demodulation of image data produced by an image sensor. In some aspects, a method includes receiving information indicating a configuration of the image sensor. In some aspects, the information may indicate a configuration of sensor elements and/or corresponding color filters for the sensor elements. A modulation function may then be generated based on the information. In some aspects, the method also includes demodulating the image data based on the generated modulation function to determine chrominance and luminance components of the image data, and generating the second image based on the determined chrominance and luminance components.

Abstract: Innovations include a sensing device having a sensor array comprising a plurality of sensors, each sensor having a length dimension and a width dimension and configured to generate a signal responsive to radiation incident on the sensor, and a filter array comprising a plurality of filters, the filter array disposed to filter light before it is incident on the sensor array, the filter array arranged relative to the sensor array so each of the plurality of sensors receives radiation propagating through at least one corresponding filter. Each filter has a length dimension and a width dimension, and a ratio of the length dimension of a filter to the length dimension of a corresponding sensor, a ratio of the width dimension of a filter to the width dimension of a corresponding sensor, or both, is a non-integer greater than 1.

Abstract: Exemplary embodiments are directed to configurable demodulation of image data produced by an image sensor. In some aspects, a method includes receiving information indicating a configuration of the image sensor. In some aspects, the information may indicate a configuration of sensor elements and/or corresponding color filters for the sensor elements. A modulation function may then be generated based on the information. In some aspects, the method also includes demodulating the image data based on the generated modulation function to determine chrominance and luminance components of the image data, and generating the second image based on the determined chrominance and luminance components.

Abstract: An electronic device for selecting a transform is described. The electronic device includes at least one image sensor, a memory, and a processor coupled to the memory and to the at least one image sensor. The processor is configured to obtain at least two images from the at least one image sensor. The processor is also configured to characterize structural content of each of the at least two images to produce a characterization for each image that is relevant to transform performance. The processor is further configured to select at least one transform from a set of transforms based on the characterization. The processor is additionally configured to apply the at least one transform to at least one of the images to substantially align the at least two images.

Abstract: Systems and method for generating depth maps using active sensing technology, for scenes with moving objects, is disclosed. One aspect provides for a method that includes estimating areas in adjacent frames that correspond to a moving object by generating a probability map for each received frame, the probability map comprising a probability value at each pixel. The method also includes computing a convex temporal average map using a plurality of the reflected structured light frames including at least the prior frame received at time t?1, the received frame received at time t, and the next frame received at time t+1, the value at each pixel of the convex temporal average map weighted and normalized by the probability map at each pixel at each time. The method also includes determining the codewords at each pixel in the convex temporal average map, and generating a depth map from the determined codewords.

Abstract: Systems and method for generating depth maps using active sensing technology, for scenes with moving objects, is disclosed. One aspect provides for a method that includes estimating areas in adjacent frames that correspond to a moving object by generating a probability map for each received frame, the probability map comprising a probability value at each pixel. The method also includes computing a convex temporal average map using a plurality of the reflected structured light frames including at least the prior frame received at time t?1, the received frame received at time t, and the next frame received at time t+1, the value at each pixel of the convex temporal average map weighted and normalized by the probability map at each pixel at each time. The method also includes determining the codewords at each pixel in the convex temporal average map, and generating a depth map from the determined codewords.

Abstract: Certain embodiments relate to systems and methods for dynamic color shading correction, which can estimate the color shading in a captured image on the fly. The color shading may be estimated from the scene statistics of the captured image, and the estimated shading may be used for color shading correction. The color shading estimation method may separate out the color shading component from the actual image content by its unique characteristic in the gradient domain.

Abstract: Aspects relate to a method of generating a high-resolution image containing depth information of an object. In one aspect, the method includes downsampling a first reference image and a second reference image from a first resolution to a second resolution, wherein the first resolution is higher than the second resolution, and wherein the first reference image and the second reference image comprising a stereo image pair. The method further includes generating a depth map at the second resolution based on global minimization techniques, using the downsampled stereo image pair. The method also includes upsampling the depth map from the second resolution to the first resolution and using a guided filter to align contours of the upsampled depth map to contours of the first reference image.

Abstract: Aspects relate to methods of generating a high-resolution image containing object depth information. A method may include capturing a first image of an object using a first camera, the first image including light projected in a known pattern on the object, extracting depth information at a first resolution from the first image, the depth information extracted based on a pattern of the projected light in the first image and capturing a second image of the scene using a second camera, the second image captured at a second resolution which is higher than the first resolution. The method also includes aligning geometries of the first and second image based on a known difference in location of the first camera and the second camera and using the second image to up-sample the depth information from the first resolution to a third resolution, the third resolution is higher than the first resolution.

Abstract: Certain aspects relate to systems and techniques for performing local intensity equalization on images in a set of images exhibiting local intensity variations. For example, the local intensity equalization can be used to perform accurate region matching and alignment of the images. The images can be partitioned into regions of pixel blocks, for instance based on location, shape, and size of identified keypoints in the images. Regions depicting the same feature in the images can be equalized with respect to intensity. Region matching based on the keypoints in the intensity-equalized regions can be performed with accuracy even in images captured by asymmetric sensors or exhibiting spatially varying intensity.