Image processing apparatus and operating method thereof

    公开(公告)号:US12190471B2

    公开(公告)日:2025-01-07

    申请号:US17723055

    申请日:2022-04-18

    Abstract: An image processing apparatus for performing image quality processing on an image includes: a memory configured to store one or more instructions; and a processor configured to execute the one or more instructions stored in the memory to: obtain a first image by downscaling an input image by using a downscale network; extract first feature information corresponding to the first image by using a feature extraction network; obtain a second image by performing image quality processing on the first image based on the first feature information, by using an image quality processing network; and obtain an output image by upscaling the second image, extracting second feature information corresponding to the input image, and performing image quality processing on the upscaled second image based on the second feature information, by using an upscale network.

    Image processing apparatus and operating method of the same

    公开(公告)号:US11380081B2

    公开(公告)日:2022-07-05

    申请号:US16861428

    申请日:2020-04-29

    Abstract: Provided is an image processing apparatus including a memory storing at least one instruction, and a processor configured to execute the at least one instruction stored in the memory to obtain first feature information by performing a convolution operation on a first image and a first kernel included in a first convolution layer among a plurality of convolution layers, obtain at least one piece of characteristic information, based on the first feature information; obtain second feature information, based on the first feature information and the at least one piece of characteristic information, obtain third feature information by performing a convolution operation on the obtained second feature information and a second kernel included in a second convolution layer that is a layer next to the first convolution layer among the plurality of convolution layers, and obtain an output image, based on the third feature information.

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