Abstract: Disclosed is a method and a system for compensating for ghosting artifacts in a display apparatus. The method includes receiving an input image intended for display on a display panel within the display apparatus. The method further includes analyzing the input image to identify pixel regions susceptible to ghosting based on proximity to an optical axis of a lens unit in the display apparatus. The method further includes calculating a compensatory color value for each pixel in the identified pixel regions using a convolution process. The compensatory color value incorporates effects of light leakage from surrounding pixels on the corresponding pixel. The method further includes applying the compensatory color values to the corresponding pixels in the identified pixel regions for generating an adjusted image. The method further includes displaying the adjusted image on the display panel of the display apparatus.

Abstract: An imaging system includes an image sensor chip with a photo-sensitive surface, photo-sensitive cells; and a colour filter array with physical smallest repeating units (PSRUs), a given PSRU having at least four sub-units, a given sub-unit comprising colour filters of at least three different colours; and at least four other colour filters whose size is equal to a size of the given sub-unit; and processor(s) configured to: obtain first image data corresponding to the at least four sub-units in individual ones of the PSRUs, while obtaining second image data corresponding to the at least four other colour filters in the individual ones of the PSRUs; and generate at least one of: a first-resolution image, a second-resolution image, a third-resolution image, a high-dynamic range (HDR) image.

Abstract: Disclosed is a method and a Head Mounted Display (HMD) for static distortion correction. The method involves collecting distortion data from an optical arrangement of the HMD, associated with a plurality of gaze directions defined by relative position of the user's pupil or head to a display screen of the HMD. The distortion data includes display pixel coordinates for display pixels and their corresponding image plane coordinates. A distortion map for each gaze direction is generated, including virtual plane coordinates of the corresponding display pixels derived from the distortion data, which are combined to form a single multi-view distortion map, calculated by a weighted average of the virtual plane coordinates across the gaze directions. The multi-view distortion map is applied to display content, ensuring distortion correction across entire field of view of the display screen of the HMD.

Abstract: Image data from an image sensor is read out, wherein when reading out, processor(s) is/are configured to employ subsampling by: reading out the image data from photo-sensitive cells that correspond to a first set of lines in a colour filter array (CFA), wherein a given line in the first set has colour filters of each of at least three different colours, the given line being a row (R1-R8) or a column (C1-C8) of the CFA; and skipping read out from photo-sensitive cells that correspond to a second set of lines in the CFA, wherein the first set of lines has one of: odd lines in the CFA, even lines in the CFA, while the second set of lines has another of: the odd lines, the even lines. The image data is processed to generate an image.

Abstract: Disclosed is an imaging system with image sensor and processor(s). The image sensor has a plurality of photo-sensitive cells and a colour filter array. The processor(s) is configured to read out unprocessed colour data from those photo-sensitive cells that correspond to the colour filters of the at least three different colours; generate coarse depth data by processing data read out from at least one of: those photo-sensitive cells that correspond to the colour filters that allow the at least one infrared wavelength to pass through the PDAF photo-sensitive cells; perform interpolation and demosaicking on the unprocessed colour data and the coarse depth data, using at least one neural network, to generate a full-resolution colour data and a full-resolution depth data; and reproject the full-resolution colour data from a given camera pose to a given eye pose of a user, by utilising the full-resolution depth data.

Abstract: A display apparatus including a display module with a display; and a gaze-tracking system with a plurality of light emitters and at least one light sensor, wherein the plurality of light emitters are arranged within a predefined region of an active area of the display module.

Abstract: An image sensor with photo-sensitive cells arranged on a photo-sensitive surface; and a colour filter array having smallest repeating units, wherein: a given smallest repeating unit has at least a first sub-unit and a second sub-unit. Image data is read out from the image sensor, wherein when reading out, processor(s) is/are configured to: selectively read out the image data from those photo-sensitive cells in a first region that correspond to respective first sub-units of smallest repeating units in the first region; and selectively skip reading out from those photo-sensitive cells in a second region that correspond to respective first sub-units of at least a first predefined percent of smallest repeating units in the second region; and process the image data to generate image(s).

Abstract: A method for deblurring distortion-corrected images, includes: obtaining a video-see-through (VST) image of a real-world environment; determining a given region of the VST image, based on at least one of: a distortion profile of a camera lens of at least one VST camera, blur characteristics of the camera lens, a scaling ratio between a resolution of the at least one VST camera and a resolution of a display whereat the VST image is to be displayed; and performing an undistortion deblurring operation on the given region of the VST image, by utilising at least one of: (i) a deblurring deconvolution filter, (ii) at least one neural network, based on locations of pixels of the given region, to generate an output image.

Abstract: Disclosed is an imaging system with an image sensor and processor(s). The image sensor has a plurality of photo-sensitive cells arranged on a photo-sensitive surface of the image sensor; a colour filter array with colour filters of at least three different colours; and a polarisation mask with polarisation filters arranged on an optical path of at most a first predefined percent of the colour filters. The processor(s) is/are configured to: read out image data from the image sensor; and process the image data to generate at least one of: a full-resolution colour image, a full-resolution polarisation image, a high-dynamic range (HDR) image.

Abstract: An optical arrangement for reducing reflections in camera includes image sensor with a light-sensitive surface and a filter arranged at a first distance from the light sensitive surface along an optical axis of optical arrangement. The filter includes a first curved surface facing a light-sensitive surface, and a second surface opposite to the first curved surface. The light-sensitive surface is configured to receive light and reflect received light towards the filter. The filter is configured to reflect light between a first curved surface and a second surface inside the filter. Reflections between the filter and the light sensitive surface are reduced.

Abstract: Image data from an image sensor is read out, wherein when reading out, processor(s) is/are configured to employ subsampling. The image data is processed, using neural network(s), to generate an image.

Abstract: A method includes detecting when a prescription lens is attached to a display apparatus; obtaining metadata associated with the prescription lens, upon the detection; determining whether the prescription lens belongs to a given set of prescription lenses that are pre-known to be compatible with the display apparatus, based on the obtained metadata; when it is determined that the prescription lens belongs to the given set of prescription lenses, obtaining at least one compensatory parameter corresponding to the prescription lens from a first data repository; and implementing prescription lens compensation by employing the at least one compensatory parameter, wherein the prescription lens compensation includes one or more of: processing at least one of: gaze-tracking data, extended-reality images to be displayed by the display apparatus, adjusting at least one physical setting of the display apparatus.

Abstract: Disclosed is a display apparatus with at least one display or projector; a gaze-tracking means; and at least one processor configured to process gaze-tracking data, collected by the gaze-tracking means, to determine a gaze direction of a user; identify a gaze region and a peripheral region within an image that is to be displayed by the at least one display or projector, based on the gaze direction; apply at least one image restoration technique on the image in an iterative manner such that M iterations of the at least one image restoration technique are applied on the gaze region, and N iterations of the at least one image restoration technique are applied on the peripheral region, M being different from N; and control the at least one display or projector to display the image having the at least one image restoration technique applied thereon.

Abstract: Disclosed is a method for enabling exposure-guided three-dimensional (3D) reconstruction, including (i) receiving Low Dynamic Range (LDR) input image captured by camera; (ii) rendering High Dynamic Range (HDR) image corresponding to input image, using HDR 3D reconstruction model pre-trained for HDR image reconstruction of 3D environment; (iii) applying HDR to LDR tone-mapping operator on HDR image, for producing tone-mapped LDR image; (iv) determining first loss function (FLF) between input image and tone-mapped LDR image, FLF comprising weighted pixel value differences between pixels of input image and corresponding pixels of tone-mapped LDR image; (v) determining whether input image has saturated pixel(s), saturated pixel(s) comprises: highlight saturated pixel, shadow saturated pixel; (vi) de-weighting pixel value difference corresponding to saturated pixel in FLF; (vii) back-propagating gradient of FLF with respect to model parameters, through differentiable render function of HDR 3D reconstruction model,

Abstract: Disclosed is a method that includes detecting a beginning of a movement of a user's gaze by processing gaze-tracking data, collected by a gaze-tracking means; predicting a motion blur in an image which is to be captured by at least one camera during the movement of the user's gaze, using a portion of the gaze-tracking data that corresponds to the beginning of the movement of the user's gaze; and compensating for the predicted motion blur while capturing the image by controlling the at least one camera.

Abstract: Image data from an image sensor (102, 202, 302, 402) is read out, wherein when reading out, processor(s) (104, 204, 304, 404) is/are configured to employ subsampling. The image data is processed, using neural network(s), to generate an image.

Abstract: A method including: obtaining images captured using camera(s), depth maps corresponding to images, and pose information; identifying image segment(s) for first image and second image; determining first relative pose of same object captured in first image; determining second relative pose of same object captured in second image; when same object is in-focus in first image, reprojecting at least image segment(s) of first image; and determining for given camera that captured second image a point spread function as function of optical depth; obtaining third image captured using given camera and third depth map corresponding to third image; and applying extended depth-of-field correction to image segment(s) of third image that is out of focus, by using point spread function.

Abstract: An imaging system has an image sensor chip and processor(s). The image sensor chip has a photo-sensitive surface with photo-sensitive cells; a colour filter array with physical smallest repeating units, wherein a given physical smallest repeating unit has array(s) of a first type of colour filters, array(s) of a second type of colour filters, and array(s) of a third type of colour filters; and a controller configured to employ neural network(s) during read out of image data. The processor(s) is/are configured to: receive output image data, wherein a smallest repeating unit in a colour pattern of at least a part of the output image data is different from the given physical smallest repeating unit; and generate an output image.

Abstract: An imaging system includes an image sensor, a wobulator employed to perform sub-pixel shifts; and processor(s) configured to: obtain, in a cycle, two or three sub-images from the image sensor; control the wobulator to perform, during said cycle, one or two sub-pixel shifts, wherein step sizes of sub-pixel shifts vary within at least one of: same cycle, different cycles, wherein at least one of step sizes is X pixel, wherein X is a fraction lying between 0 and 1, at least one other of step sizes is Y pixels, wherein Y is an integer lying in a range from 1 to Z, Z being equal to a number of pixels of same colour lying along a direction of sub-pixel shift in a smallest repeating M×N array (204a-b) in the image sensor; and process the two or three sub-images to generate image(s).

Abstract: Disclosed is system (100) comprising at least one server (102) configured to: obtain at least two images of real-world environment whose fields of view overlap at least partially; obtain pose information indicative of corresponding camera poses from which at least two images are captured; detect, in at least two images, at least one object (202A-202G) that is in contact with given plane (204, 208) present in real-world environment; identify, in at least two images, same features (206A-206J) of at least one object that lie on given plane; determine poses of same features, wherein pose of given same feature is determined, based on disparity in two-dimensional positions of given same feature in at least two images and corresponding camera poses from which at least two images are captured; and estimate given plane based on poses of same features.