Samsung Electronics Co., Ltd.

Soomin Kang

Tammy Lee

Hanul Shin

Iljun Ahn

Jaeyeon Park

Youngchan Song

IIjun Ahn

An image processing apparatus for performing an image by using one or more neural networks may include a memory storing one or more instructions and at least one processor configured to execute the one or more instructions stored in the memory to obtain first feature information of a first image, generate an intermediate output image for the first image by performing first image processing on the first feature information, generate an attention map, based on the first image and the intermediate output image, obtain second feature information by performing second image processing on the first feature information, obtain fourth feature information by performing third image processing on third feature information extracted during the first image processing, and generate a second image having a higher quality than the first image, based on the attention map, the second feature information, and the fourth feature information.

Image processing apparatus and operation method thereof for obtaining high quality image

An image processing apparatus may include: a memory storing one or more instructions; and a processor configured to execute the one or more instructions stored in the memory, wherein the processor executes the one or more instructions to use one or more convolutional neural networks to: determine first parameters, based on position information of first pixels included in a first region of a first image and position information of samples of the first image; obtain sample values of the samples by applying the first parameters to pixel values of the first pixels; obtain feature information corresponding to the first region by performing a convolution operation between the sample values and a kernel of the one or more convolutional neural networks; and generate a second image, based on the feature information.

Image processing apparatus and operation method thereof

An image processing apparatus, including a processor configured to execute instructions stored in a memory to: obtain characteristic information of a first image, divide the characteristic information into a plurality of groups, input each group into a respective layer of a plurality of layers included in a convolutional neural network and perform a convolution operation using one or more kernels to obtain a plurality of pieces of output information, generate an attention map including weight information corresponding to each pixel included in the first image, based on the plurality of pieces of output information, generate a spatially variant kernel including a kernel corresponding to the each pixel, based on the attention map and a spatial kernel including weight information according to a position relationship between the each pixel and a neighboring pixel, and generate a second image by applying the spatially variant kernel to the first image.

Image processing apparatus and operating method thereof

An image processing apparatus and a method of operating the same are provided. The method includes: a memory storing one or more instructions; and a processor configured to execute the one or more instructions stored in the memory to obtain first frequency coefficient information by converting a first image into a frequency domain in units of blocks having a preset size, obtain correlation information indicating a correlation between at least one block of the first frequency coefficient information and a first kernel, generate a weight corresponding to the first frequency coefficient information based on the correlation information, generate second frequency coefficient information by rearranging coefficients included in the first frequency coefficient information, wherein the one or more of the coefficients having a same frequency is arranged into a same group, and obtain quality information of the first image based on the weight and the second frequency coefficient information.

Image processing apparatus and operating method of the same

An image processing apparatus, including a memory configured to store one or more instructions; and at least one processor configured to execute the one or more instructions to: based on a first image and a probability model, optimize an estimated pixel value and estimated gradient values of each pixel of an original image corresponding to the first image, obtain an estimated original image based on the optimized estimated pixel value of the each pixel of the original image, obtain a decontour map based on the optimized estimated pixel value and the estimated gradient values of the each pixel of the original image, and generate a second image by combining the first image with the estimated original image based on the decontour map.

An image processing device, including 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 kernel coefficient information corresponding to each pixel of a plurality of pixels included in a first image, using a convolution neural network including one or more convolution layers, generate a spatially variant kernel including a kernel corresponding to the each pixel, based on a gradient kernel set including a plurality of gradient kernels corresponding to one or more gradient characteristics of the plurality of pixels, and the kernel coefficient information, and generate a second image, by applying the kernel included in the spatially variant kernel to a region centered on the each pixel, and filtering the first image.

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Suwon-si, South Korea

Soomin Kang