A method includes capturing, by a camera disposed behind a display panel of an electronic device, an original image through a semi-transparent pixel region of the display panel. The original image includes one or more color components. The method further includes determining, for a plurality of pixel regions of the original image, a point spread function (PSF) for each of the one or more color components. The method further includes performing, for the plurality of pixel regions of the original image, a deconvolution of each of the one or more color components of the original image based at least in part on their respective PSFs. The method thus includes generating a reconstructed image corresponding to the original image based on the deconvolutions of the one or more color components of the plurality of pixel regions of the original image.

A lens unit (120) shows longitudinal chromatic aberration and focuses an imaged scene into a first image for the infrared range in a first focal plane and into a second image for the visible range in a second focal plane. An optical element (150) manipulates the modulation transfer function assigned to the first and second images to extend the depth of field. An image processing unit (200) may amplify a modulation transfer function contrast in the first and second images. A focal shift between the focal planes may be compensated for. While in conventional approaches for RGBIR sensors contemporaneously providing both a conventional and an infrared image of the same scene the infrared image is severely out of focus, the present approach provides extended depth of field imaging to rectify the problem of out-of-focus blur for infrared radiation. An imaging system can be realized without any apochromatic lens.

One variation of a method for segmenting scenes of product units arranged in inventory structures within a store includes: accessing an image based on data captured by a mobile robotic system; detecting a shelving segment in the image; reading a segment identifier from a segment tag, detected in the image, arranged on the shelving segment; accessing a product template representing a product type in the set of product types assigned to the shelving segment based on the segment identifier; detecting a set of product features, in the first region of the image. In response to detecting the set of product features analogous to features of the product template: confirming presence of the unit of the first product type on the shelf in the shelving segment and appending the first product type to a list of product types presently stocked in the shelving segment.

A method includes obtaining an input image that contains a particular representation of lens flare, and processing the input image by a machine learning model to generate a de-flared image that includes the input image with at least part of the particular representation of lens flare removed. The machine learning (ML) model may be trained by generating training images that combine respective baseline images with corresponding lens flare images. For each respective training image, a modified image may be determined by processing the respective training image by the ML model, and a loss value may be determined based on a loss function comparing the modified image to a corresponding baseline image used to generate the respective training image. Parameters of the ML model may be adjusted based on the loss value determined for each respective training image and the loss function.

In one implementation, an apparatus includes a display having a front surface and a back surface. The display includes a plurality of pixel regions that emit light from the front surface to display a displayed image and a plurality of apertures that transmit light from the front surface to the back surface. The apparatus includes a camera disposed on a side of the back surface of the display. The camera is configured to capture a captured image. The apparatus includes a processor coupled to the display and the camera. The processor is configured to receive the captured image and apply a first digital filter to a first portion of the captured image and a second digital filter, different than the first digital filter, to a second portion of the captured image to reduce image distortion caused by the display.

A method and apparatus for capturing digital video includes displaying a preview of a field of view of the imaging device in a user interface of the imaging device. A sequence of images is captured. A main subject and a background in the sequence of images is determined, wherein the main subject is different than the background. A sequence of modified images for use in a final video is obtained, wherein each modified image is obtained by combining two or more images of the sequence of images such that the main subject in the modified image is blur free and the background is blurred. The sequence of modified images is combined to obtain the final video, which is stored in a memory of the imaging device, and displayed in the user interface.

A method and apparatus for capturing digital video includes displaying a preview of a field of view of the imaging device in a user interface of the imaging device. A sequence of images is captured. A main subject and a background in the sequence of images is determined, wherein the main subject is different than the background. A sequence of modified images for use in a final video is obtained, wherein each modified image is obtained by combining two or more images of the sequence of images such that the main subject in the modified image is blur free and the background is blurred. The sequence of modified images is combined to obtain the final video, which is stored in a memory of the imaging device, and displayed in the user interface.

A method and apparatus for capturing digital video includes displaying a preview of a field of view of the imaging device in a user interface of the imaging device. A sequence of images is captured. A main subject and a background in the sequence of images is determined, wherein the main subject is different than the background. A sequence of modified images for use in a final video is obtained, wherein each modified image is obtained by combining two or more images of the sequence of images such that the main subject in the modified image is blur free and the background is blurred. The sequence of modified images is combined to obtain the final video, which is stored in a memory of the imaging device, and displayed in the user interface.

A method for stray light compensation is disclosed. The method comprising: acquiring a first image with a first imaging device covering a first field-of-view; acquiring a second image with a second imaging device covering a second field-of-view, wherein the second field-of-view is larger than the first field-of-view and wherein the first field-of-view is included in the second field-of-view; estimating stray light components in pixels of the first image from pixel data of pixels in the second image; and compensating for stray light in the first image by subtracting the estimated stray light components in pixels of the first image. Also, a system for stray light compensation is disclosed.

An image processing apparatus includes a determination unit configured to determine an optical transfer function based on shooting condition information, an acquisition unit configured to acquire shake information, a control unit configured to select a method of image restoration based on the optical transfer function and the shake information, and an image restoration unit configured to perform the image restoration based on the selected method of the image restoration.