Abstract: A method for super resolution of an image imitating optical zoom implemented on a resource-constrained mobile device is includes inputting a first-resolution image. The method also includes assigning a super resolution factor from a predefined set of super resolution factors that indicate increasing the first resolution to obtain a second-resolution image. The super resolution factor indicates a trained intelligent system imitating the operation of the corresponding optical system among a plurality of intelligent systems trained for each super resolution factor of the predefined set of super resolution factors. The method further includes transforming the first-resolution image into the second-resolution image using said trained intelligent system.

Abstract: A method and an illumination manipulation device of performing an object illumination manipulation operation on a first image are provided. The method includes receiving the first image and an input of a light direction, generating a second image with a first object detected from the first image, determining a second object illumination of the second image based on the light direction and replacing a first object illumination of the first image with the second object illumination.

Abstract: Provided is a magnetic resonance imaging (MRI) apparatus including an acquisition unit configured to acquire an undersampled spectrum in a k-space and a reconstruction unit configured to generate a target image based on the undersampled spectrum, wherein the reconstruction unit includes: a first sub-reconstruction unit configured to perform initial reconstruction on data corresponding to unsampled positions in the k-space by using a Split Bregman algorithm or approximate sparse coding; a second sub-reconstruction unit configured to decompose the initially reconstructed spectrum in the k-space into multiple frequency bands to thereby generate a plurality of individual spectra and perform dictionary learning reconstruction on images respectively corresponding to the decomposed multiple frequency bands by alternating sparse approximation and reconstructing of measured frequencies; and an image generator configured to generate a target image by merging together the reconstructed images respectively corresponding

Abstract: A method for super resolution of an image imitating optical zoom implemented on a resource-constrained mobile device is includes inputting a first-resolution image. The method also includes assigning a super resolution factor from a predefined set of super resolution factors that indicate increasing the first resolution to obtain a second-resolution image. The super resolution factor indicates a trained intelligent system imitating the operation of the corresponding optical system among a plurality of intelligent systems trained for each super resolution factor of the predefined set of super resolution factors. The method further includes transforming the first-resolution image into the second-resolution image using said trained intelligent system.

Abstract: A method and an illumination manipulation device of performing an object illumination manipulation operation on a first image are provided. The method includes receiving the first image and an input of a light direction, generating a second image with a first object detected from the first image, determining a second object illumination of the second image based on the light direction and replacing a first object illumination of the first image with the second object illumination.

Abstract: Provided are a magnetic resonance (MR) image processing apparatus and a method of reconstructing a MR image. The MR image processing apparatus includes a processor and a memory connected to the processor, wherein the processor is configured to acquire a partially sampled multi-coil k-space with respect to an object and obtain a reconstructed image of the object by reconstructing the partially sampled multi-coil k-space based on a pre-acquired first dictionary and a second dictionary acquired by using the first dictionary.

Abstract: Provided is a magnetic resonance imaging (MRI) apparatus including an acquisition unit configured to acquire an undersampled spectrum in a k-space and a reconstruction unit configured to generate a target image based on the undersampled spectrum, wherein the reconstruction unit includes: a first sub-reconstruction unit configured to perform initial reconstruction on data corresponding to unsampled positions in the k-space by using a Split Bregman algorithm or approximate sparse coding; a second sub-reconstruction unit configured to decompose the initially reconstructed spectrum in the k-space into multiple frequency bands to thereby generate a plurality of individual spectra and perform dictionary learning reconstruction on images respectively corresponding to the decomposed multiple frequency bands by alternating sparse approximation and reconstructing of measured frequencies; and an image generator configured to generate a target image by merging together the reconstructed images respectively corresponding