Abstract:
An image coding method and apparatus considering human visual characteristics are provided. The image coding method comprises (a) modeling image quality distribution of an input image in units of scenes such that the quality of an image input in units of scenes is gradually lowered from a region of interest to a background region, (b) determining a quantization parameter of each region constituting one scene according to the result of modeling of image quality distribution, (c) quantizing image data in accordance with the quantization parameter, and (d) coding entropy of the quantized image data.
Abstract:
A video encoding method and apparatus and a video decoding method and apparatus are provided. The video encoding method includes: prediction encoding in units of a coding unit as a data unit for encoding a picture, by using partitions determined based on a first partition mode and a partition level, so as to select a partition for outputting an encoding result from among the determined partitions; and encoding and outputting partition information representing a first partition mode and a partition level of the selected partition. The first partition mode represents a shape and directionality of a partition as a data unit for performing the prediction encoding on the coding unit, and the partition level represents a degree to which the coding unit is split into partitions for detailed motion prediction.
Abstract:
A convolutional neural network-based image processing method is provided. The method includes: receiving, in a second layer, multi-channel feature map images generated by applying a convolution operation to an input image of a convolutional neural network having a plurality of layers with a plurality of filter kernels of a first layer; analyzing a dynamic range of the multi-channel feature map images; re-ordering the multi-channel feature map images, based on the dynamic range; and processing the re-ordered multi-channel feature map images in the second layer.
Abstract:
An image coding method and apparatus considering human visual characteristics are provided. The image coding method comprises (a) modeling image quality distribution of an input image in units of scenes such that the quality of an image input in units of scenes is gradually lowered from a region of interest to a background region, (b) determining a quantization parameter of each region constituting one scene according to the result of modeling of image quality distribution, (c) quantizing image data in accordance with the quantization parameter, and (d) coding entropy of the quantized image data.
Abstract:
An image coding method and apparatus considering human visual characteristics are provided. The image coding method comprises (a) modeling image quality distribution of an input image in units of scenes such that the quality of an image input in units of scenes is gradually lowered from a region of interest to a background region, (b) determining a quantization parameter of each region constituting one scene according to the result of modeling of image quality distribution, (c) quantizing image data in accordance with the quantization parameter, and (d) coding entropy of the quantized image data.
Abstract:
A method, medium, and apparatus encoding and/or decoding an image in order to increase encoding and decoding efficiency by performing binary-arithmetic coding/decoding on a binary value of a syntax element using a probability model having the same syntax element probability value for respective context index information of each of at least two image components.
Abstract:
An image coding method and apparatus considering human visual characteristics are provided. The image coding method comprises (a) modeling image quality distribution of an input image in units of scenes such that the quality of an image input in units of scenes is gradually lowered from a region of interest to a background region, (b) determining a quantization parameter of each region constituting one scene according to the result of modeling of image quality distribution, (c) quantizing image data in accordance with the quantization parameter, and (d) coding entropy of the quantized image data.
Abstract:
A method, medium, and system encoding and/or decoding a moving picture. The moving picture encoding method may include selecting a prediction mode that is optimal for the macro blocks, which correspond to each other, of the color components of a current image based on the characteristics of a predetermined image, generating a predicted image for the current image according to the selected prediction mode, and encoding a moving picture using the predicted image. An optimal prediction mode can be adaptively applied to the macro blocks, which correspond to each other, of the color components, thereby increasing the moving picture's encoding and decoding efficiencies.
Abstract:
A method, medium, and system encoding and/or decoding a moving picture. The moving picture encoding method may include selecting a prediction mode that is optimal for the macro blocks, which correspond to each other, of the color components of a current image based on the characteristics of a predetermined image, generating a predicted image for the current image according to the selected prediction mode, and encoding a moving picture using the predicted image. An optimal prediction mode can be adaptively applied to the macro blocks, which correspond to each other, of the color components, thereby increasing the moving picture's encoding and decoding efficiencies.
Abstract:
An image coding method and apparatus considering human visual characteristics are provided. The image coding method comprises (a) modeling image quality distribution of an input image in units of scenes such that the quality of an image input in units of scenes is gradually lowered from a region of interest to a background region, (b) determining a quantization parameter of each region constituting one scene according to the result of modeling of image quality distribution, (c) quantizing image data in accordance with the quantization parameter, and (d) coding entropy of the quantized image data.