Method and apparatus for processing an image

    公开(公告)号:US11816817B2

    公开(公告)日:2023-11-14

    申请号:US17831032

    申请日:2022-06-02

    Abstract: A method includes: obtaining a plurality of view images; identifying a representative value from among difference values between values of a plurality of sub-pixels corresponding to a first position in the plurality of view images and an intermediate value of a bit range of a display; determining filtering strength corresponding to the representative value, based on a correspondence map indicating a correspondence relationship between filtering strength and a difference value between a value of a sub-pixel and the intermediate value; and applying a filter having the determined filtering strength to the plurality of sub-pixels corresponding to the first position, wherein a value resulting from applying the filter having the determined filtering strength to the plurality of sub-pixels corresponding to the first position is included in a range of sub-pixel values according to the bit range of the display.

    Electronic apparatus and control method thereof

    公开(公告)号:US11575882B2

    公开(公告)日:2023-02-07

    申请号:US17135247

    申请日:2020-12-28

    Abstract: An electronic apparatus includes a stacked display including a plurality of panels, and a processor configured to obtain first light field (LF) images of different viewpoints, input the obtained first LF images to an artificial intelligence model for converting an LF image into a layer stack, to obtain a plurality of layer stacks to which a plurality of shifting parameters indicating depth information in the first LF images are respectively applied, and control the stacked display to sequentially and repeatedly display, on the stacked display, the obtained plurality of layer stacks. The artificial intelligence model is trained by applying the plurality of shifting parameters that are obtained based on the depth information in the first LF images.

    Display apparatus and the control method thereof

    公开(公告)号:US11917124B2

    公开(公告)日:2024-02-27

    申请号:US17696423

    申请日:2022-03-16

    CPC classification number: H04N13/398 G02B30/10 H04N13/125 H04N13/302

    Abstract: A display apparatus and a controlling method thereof are provided. The display apparatus includes a display comprising a first display panel, a lens array disposed on the first display panel, and a second display panel disposed on the lens array; and a processor to, based on a plurality of light field (LF) images, obtain a left (L) image and a right (R) image to drive the display by time-multiplexing, correct a second L image to drive the second display panel among the L images based on a first R image to drive the first display panel among the R images, and correct a second R image to drive the second display panel among the R images based on the first L image to drive the first display panel among the L images, and display a stereoscopic image by driving the display by time-multiplexing based on the L image which includes the corrected second L image and the R image which includes the corrected second R image. The display apparatus of the disclosure may use an artificial intelligence model trained according to at least one of a rule-based model, a machine learning, a neural network, or a deep learning algorithm.

    ELECTRONIC APPARATUS AND CONTROL METHOD THEREOF

    公开(公告)号:US20210203917A1

    公开(公告)日:2021-07-01

    申请号:US17135247

    申请日:2020-12-28

    Abstract: An electronic apparatus includes a stacked display including a plurality of panels, and a processor configured to obtain first light field (LF) images of different viewpoints, input the obtained first LF images to an artificial intelligence model for converting an LF image into a layer stack, to obtain a plurality of layer stacks to which a plurality of shifting parameters indicating depth information in the first LF images are respectively applied, and control the stacked display to sequentially and repeatedly display, on the stacked display, the obtained plurality of layer stacks. The artificial intelligence model is trained by applying the plurality of shifting parameters that are obtained based on the depth information in the first LF images.

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