Abstract:
A hierarchical motion prediction apparatus and method. The hierarchical motion prediction method splits a current frame and a reference frame into pixel groups, changes a pixel location of each pixel group, and selects one pixel, and thus resolutions of the current frame and reference frame are reduced. A motion vector of a down-sampled current block is obtained based on a down-sampled current frame and reference frame, and is expanded to a motion vector of an original resolution based on a down sampling rate.
Abstract:
An electronic apparatus is provided. The electronic apparatus includes: a storage configured to store a plurality of filters each corresponding to a plurality of image patterns; and a processor configured to classify an image block including a target pixel and a plurality of surrounding pixels into one of the plurality of image patterns based on a relationship between pixels within the image block and to obtain a final image block in which the target pixel is image-processed by applying at least one filter corresponding to the classified image pattern from among the plurality of filters to the image block, wherein the plurality of filters are obtained by learning, through an artificial intelligence algorithm, a relationship between a plurality of first sample image blocks and a plurality of second sample image blocks corresponding to the plurality of first sample image blocks based on each of the plurality of image patterns.
Abstract:
A display apparatus is provided. The display apparatus includes an input interface, a first storage, a display, and a processor. Pixel values corresponding to a predetermined number of lines in an image input through the input interface are stored in the first storage,. The processor acquires a first patch of a predetermined size by sampling a number of pixel values located in an outer region of a matrix centering about a specific pixel value from among the pixel values stored in the first storage, acquires a high-frequency component for the specific pixel value based on the acquired first patch, and processes the input image based on the high-frequency component. The display displays the processed image.
Abstract:
An electronic apparatus is provided. The electronic apparatus includes: a storage configured to store a plurality of filters each corresponding to a plurality of image patterns; and a processor configured to classify an image block including a target pixel and a plurality of surrounding pixels into one of the plurality of image patterns based on a relationship between pixels within the image block and to obtain a final image block in which the target pixel is image-processed by applying at least one filter corresponding to the classified image pattern from among the plurality of filters to the image block, wherein the plurality of filters are obtained by learning, through an artificial intelligence algorithm, a relationship between a plurality of first sample image blocks and a plurality of second sample image blocks corresponding to the plurality of first sample image blocks based on each of the plurality of image patterns.
Abstract:
A motion vector estimation method of a motion vector estimation apparatus are provided. The motion vector estimation method of the motion vector estimation apparatus includes: determining a motion vector of a current block by setting, in another frame, a local search area for searching a plurality of reference pixel blocks corresponding to the current block which is one of pixel blocks in a single frame; and finally determining one of the determined motion vector and a previous motion vector referred to in order to determine the local search area as a motion vector of the current block, based on sum of absolution difference (SAD) values of the reference pixel blocks included in the local search area.