An electronic apparatus comprising: a storage configured to store a compression rate network model configured to identify a compression rate applied to an image block from among a plurality of compression rates, and a plurality of compression noise removing network models configured to remove compression noise for each of the plurality of compression rates; and a processor configured to: obtain a compression rate of each of a plurality of image blocks included in a frame of a decoded moving picture based on the compression rate network model, obtain a compression rate of the frame based on the plurality of obtained compression rates, and remove compression noise of the frame based on a compression noise removing network model corresponding to the compression rate of the frame from among the plurality of compression noise removing network models, wherein the compression rate network model is obtained by learning image characteristics of a plurality of restored image blocks corresponding to the plurality of compression rates through a first artificial intelligence algorithm, wherein the plurality of restored image blocks are generated by encoding a plurality of original image blocks, and decoding the encoded plurality of original image blocks, and wherein the plurality of compression noise removing network models are obtained by learning a relation between the plurality of original image blocks and the plurality of restored image blocks through a second artificial intelligence algorithm. a storage configured to store a compression rate network model configured to identify a compression rate applied to an image block from among a plurality of compression rates, and a plurality of compression noise removing network models configured to remove compression noise for each of the plurality of compression rates; and a processor configured to: obtain a compression rate of each of a plurality of image blocks included in a frame of a decoded moving picture based on the compression rate network model, obtain a compression rate of the frame based on the plurality of obtained compression rates, and remove compression noise of the frame based on a compression noise removing network model corresponding to the compression rate of the frame from among the plurality of compression noise removing network models, wherein the compression rate network model is obtained by learning image characteristics of a plurality of restored image blocks corresponding to the plurality of compression rates through a first artificial intelligence algorithm, wherein the plurality of restored image blocks are generated by encoding a plurality of original image blocks, and decoding the encoded plurality of original image blocks, and wherein the plurality of compression noise removing network models are obtained by learning a relation between the plurality of original image blocks and the plurality of restored image blocks through a second artificial intelligence algorithm. obtain a compression rate of each of a plurality of image blocks included in a frame of a decoded moving picture based on the compression rate network model, obtain a compression rate of the frame based on the plurality of obtained compression rates, and remove compression noise of the frame based on a compression noise removing network model corresponding to the compression rate of the frame from among the plurality of compression noise removing network models, wherein the compression rate network model is obtained by learning image characteristics of a plurality of restored image blocks corresponding to the plurality of compression rates through a first artificial intelligence algorithm, wherein the plurality of restored image blocks are generated by encoding a plurality of original image blocks, and decoding the encoded plurality of original image blocks, and wherein the plurality of compression noise removing network models are obtained by learning a relation between the plurality of original image blocks and the plurality of restored image blocks through a second artificial intelligence algorithm.