Abstract: An image processing device and an operating method of the image processing device are disclosed. The image processing device includes a multimedia intellectual property (IP) configured to generate second image data by performing image processing on first image data and an encoder configured to compress the second image data, the encoder is further configured to generate first compressed data by performing quantization and at least one compression processing on a first block of the second image data based on a target compression ratio in a first compression condition, and generate second compressed data by performing the quantization on a second block of the second image data based on a first quantization step in a second compression condition, without performing the at least one compression processing.

Abstract: An image encoder for outputting a bitstream by encoding an input image includes a predictive block, a machine learning based prediction enhancement (MLBE) block, and a subtractor. The predictive block is configured to generate a prediction block using data of a previous input block. The MLBE block is configured to transform the prediction block into an enhanced prediction block by applying a machine learning technique to the prediction block. The subtractor is configured to generate a residual block by subtracting pixel data of the enhanced prediction block from pixel data of a current input block.

Abstract: A video encoding method of estimating a motion vector of a current block in a current frame includes identifying a reference block in a reference frame, a first location of the current block within the current frame corresponding to a second location of the reference block within the reference frame, setting a search range in the reference frame, searching for candidate blocks from the search range of the reference frame, each of the candidate blocks satisfying a corresponding first motion estimation criterion of first motion estimation criteria, searching for a prediction block from among the candidate blocks, the prediction block satisfying a second motion estimation criterion, estimating, as the motion vector of the current block, a motion vector corresponding to a displacement between the reference block and the prediction block, and encoding the current block based on the estimated motion vector.

Abstract: An image encoder for outputting a bitstream by encoding an input image includes a predictive block, a machine learning based prediction enhancement (MLBE) block, and a subtractor. The predictive block is configured to generate a prediction block using data of a previous input block. The MLBE block is configured to transform the prediction block into an enhanced prediction block by applying a machine learning technique to the prediction block. The subtractor is configured to generate a residual block by subtracting pixel data of the enhanced prediction block from pixel data of a current input block.

Abstract: An image encoder for outputting a bitstream by encoding an input image includes a predictive block, a machine learning based prediction enhancement (MLBE) block, and a subtractor. The predictive block is configured to generate a prediction block using data of a previous input block. The MLBE block is configured to transform the prediction block into an enhanced prediction block by applying a machine learning technique to the prediction block. The subtractor is configured to generate a residual block by subtracting pixel data of the enhanced prediction block from pixel data of a current input block.

Abstract: An electronic circuit includes a block determinator, a candidate selector, and a motion vector generator to perform motion estimation. The block determinator determines a current block and candidate blocks with regard to each of decimated images generated from an original image, wherein the block determinator determines first candidate blocks based on a location of the current block without a full search for all pixels with regard to a first decimated image of the lowest resolution. The candidate selector selects second candidate blocks which are some of the first candidate blocks with regard to a second decimated image of the highest resolution, such that the block determinator determines the second candidate blocks with regard to the original image. The motion vector generator generates a motion vector for the current block based on one reference patch determined from reference patches indicated by candidate motion vectors of the second candidate blocks.

Abstract: An electronic circuit includes a block determinator, a candidate selector, and a motion vector generator to perform motion estimation. The block determinator determines a current block and candidate blocks with regard to each of decimated images generated from an original image, wherein the block determinator determines first candidate blocks based on a location of the current block without a full search for all pixels with regard to a first decimated image of the lowest resolution. The candidate selector selects second candidate blocks which are some of the first candidate blocks with regard to a second decimated image of the highest resolution, such that the block determinator determines the second candidate blocks with regard to the original image. The motion vector generator generates a motion vector for the current block based on one reference patch determined from reference patches indicated by candidate motion vectors of the second candidate blocks.

Abstract: A video encoding apparatus includes at least one processor. The at least one processor is configured to adjust a size of a first quantization parameter with reference to a characteristic of quantization coefficients generated from input data by using the first quantization parameter, to determine the first quantization parameter of the adjusted size as a final quantization parameter, and to quantize the input data by using the final quantization parameter to generate output data.

Abstract: A video encoding apparatus includes at least one processor. The at least one processor is configured to adjust a size of a first quantization parameter with reference to a characteristic of quantization coefficients generated from input data by using the first quantization parameter, to determine the first quantization parameter of the adjusted size as a final quantization parameter, and to quantize the input data by using the final quantization parameter to generate output data.

Abstract: An image encoder for outputting a bitstream by encoding an input image includes a predictive block, a machine learning based prediction enhancement (MLBE) block, and a subtractor. The predictive block is configured to generate a prediction block using data of a previous input block. The MLBE block is configured to transform the prediction block into an enhanced prediction block by applying a machine learning technique to the prediction block. The subtractor is configured to generate a residual block by subtracting pixel data of the enhanced prediction block from pixel data of a current input block.

Abstract: The inventive concept relates to an encoding method of encoding image data of a frame including a plurality of image blocks. The encoding method includes selecting a first image block as the main image block of a first window, selecting a first window having to perform a plurality of loop filtering schemes on image data of the selected window. The loop filtering schemes includes a deblocking filtering, a sample adaptive offset filtering, and an adaptive loop filtering. The perimeter of the selected first window does not coincide with the perimeter of the first image block.