Abstract: 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.

Abstract: 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.

Abstract: Provided is a method of processing a video, the method comprising: extracting a first image feature from a first input image included in a scene, extracting a second image feature from a second input image included in the scene, wherein the second input image is a target frame, generating, based on the first image feature and the second image feature, a temporal feature associated with information about a temporal change between the first image feature and the second image feature, and generating an output image based on the temporal feature.

Abstract: An electronic device for generating an image with an enhanced depth as perceived by a viewer includes at least one memory storing instructions, and at least one processor configured to execute the instructions to receive an input image, receive a control parameter for adjusting a first level of at least one pictorial depth cue included in the input image, and generate an output image including the at least one pictorial depth cue at a second level that is adjusted from the first level based on the control parameter using a deep neural network.

Abstract: 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 to obtain classification information of a first image and first feature information of the first image, generate a first feature image for the first image by performing first image processing on the classification information and the first feature information, obtain second feature information by performing second image processing on the classification information and the first feature information, obtain fourth feature information by performing third image processing on third feature information extracted during the first image processing, generate a second feature image for the first image, based on the second feature information and the fourth feature information, and generate a second image based on the first feature image and the second feature image.

Abstract: 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.

Abstract: An image processing apparatus for processing an image by using one neural network, includes: a memory storing one instruction; and one processor configured to execute the one instruction to: obtain first feature data, based on a first image, obtain pieces of second feature data corresponding to first areas of the first image by performing first image processing on the first feature data, the first areas comprising a first number of pixels, obtain third feature data, based on the first image, obtain pieces of fourth feature data corresponding to second areas of the first image, by performing second image processing on the third feature data, the second areas comprising a second number of pixels that is greater than the first number, and generate a second image, based on the pieces of second feature data and the pieces of fourth feature data.

Abstract: An image processing apparatus includes: a memory storing one or more instructions; and a processor configured to execute the one or more instructions to: obtain similarity information, based on a pixel difference between each pixel included in a first image and an adjacent pixel of each pixel included in the first image; determine weight information based on the similarity information; obtain first feature information by performing a convolution operation between the first image and a first kernel; obtain second feature information by applying the weight information to the first feature information; and generate a second image based on the second feature information.

Abstract: An image processing apparatus for processing an image by using one or more convolutional neural networks includes 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 data by performing a convolution operation between input data obtained from a first image and a first kernel, divide a plurality of channels included in the first feature data into first groups, obtain second feature data by performing a convolution operation between the first feature data respectively corresponding to the first groups and second kernels respectively corresponding to the first groups, obtain shuffling data by shuffling the second feature data, obtain output data by performing a convolution operation between data obtained by summing channels included in the shuffling data and a third kernel, and generate a second image based on the output data.

Abstract: 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.

Abstract: 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.

Abstract: An image processing apparatus, 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 similarity information indicating a similarity between each pixel of a plurality of pixels included in a first image and an adjacent pixel of the each pixel; generate a weight map including weight information corresponding to the each pixel, based on the similarity information; generate a spatially variant kernel including a plurality of kernels corresponding to the plurality of pixels, based on the weight map and a spatial kernel including weight information based on a location relationship between the each pixel and the adjacent pixel; and generate a second image by applying the spatially variant kernel to the first image.