Abstract: The present application relates to an information processing device and method, and a computer readable storage medium. The information processing device comprises a processing circuit, configured to generate a composite noise image on the basis of an input original image, process the black level in the composite noise image, and train, on the basis of the processed composite noise image, a machine learning model used for image denoising, to obtain a trained machine learning model.

Abstract: The present disclosure relates to an apparatus, a method, and a storage medium for federated learning (FL). Various embodiments for FL are described. In an embodiment, a central processing apparatus can be configured to, for a first one of a plurality of distributed computing apparatuses: receive a report message from the first distributed computing apparatus, the report message including at least one of training data set information or device information of the first distributed computing apparatus; evaluate FL performance of the first distributed computing apparatus based on the report message of the first distributed computing apparatus; determine wireless resource requirements of the first distributed computing apparatus based on the FL performance of the first distributed computing apparatus; and notify a wireless network, via a message, of configuring wireless resources for the first distributed computing apparatus based on the wireless resource requirements.

Abstract: A method and corresponding apparatus include extracting a movement trajectory feature of an object from an input video. The method and corresponding apparatus also include coding the extracted movement trajectory feature, and determining a type of a movement of the object based on the coded movement trajectory feature.

Abstract: An image processing method includes configuring a noise reduction filter for each of pixels in an image in accordance with a linear noise model of the image, based on different levels of a noise effect caused to a corresponding pixel, among the pixels, by other pixels, among the pixels and adjacent to the corresponding pixel. The method further includes performing noise reduction filtering on each of the pixels, using the noise reduction filter for each of the pixels, to obtain a noise reduced image.

Abstract: A method of enhancing a quality of a 3 dimensional (3D) image includes classifying an input 3D image into a plurality of sub-areas based on noise characteristics of the plurality of sub-areas of the input 3D image, denoising each of the plurality of sub-areas of the input 3D image by using different denoising methods according to noise characteristics of each of the classified plurality of sub-areas and obtaining a second 3D image after the denoising, and enhancing a contrast ratio of the second 3D image after the denoising.

Abstract: A method and corresponding apparatus include extracting a movement trajectory feature of an object from an input video. The method and corresponding apparatus also include coding the extracted movement trajectory feature, and determining a type of a movement of the object based on the coded movement trajectory feature.

Abstract: A method of enhancing a quality of a 3 dimensional (3D) image includes classifying an input 3D image into a plurality of sub-areas based on noise characteristics of the plurality of sub-areas of the input 3D image, denoising each of the plurality of sub-areas of the input 3D image by using different denoising methods according to noise characteristics of each of the classified plurality of sub-areas and obtaining a second 3D image after the denoising, and enhancing a contrast ratio of the second 3D image after the denoising.

Abstract: An image processing method includes configuring a noise reduction filter for each of pixels in an image in accordance with a linear noise model of the image, based on different levels of a noise effect caused to a corresponding pixel, among the pixels, by other pixels, among the pixels and adjacent to the corresponding pixel. The method further includes performing noise reduction filtering on each of the pixels, using the noise reduction filter for each of the pixels, to obtain a noise reduced image.