Method and apparatus for super resolution
AssigneeSamsung Electronics Co., Ltd.
InventorsYounghyun Jo, Sehwan Ki, Eunhee Kang, Hyong Euk Lee
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Abstract
Systems and methods for super-resolution (SR) are described. The SR method includes determining a direction type of an input image based on a gradient of the input image, obtaining a first intermediate image based on the direction type using a look-up table (LUT) that stores an SR operation result of a pixel value combination corresponding to a kernel set mapped to the determined direction type, wherein the first intermediate image is an SR image corresponding to the input image, applying SR interpolation to the input image to obtain a baseline image, and obtaining an output image based on the first intermediate image and the baseline image.
Claims20
A method of performing super-resolution (SR), comprising:
- determining a direction type of an input image based on a gradient of the input image;
- obtaining a first intermediate image based on the direction type using a look-up table (LUT) that stores an SR operation result of a pixel value combination corresponding to a kernel set mapped to the determined direction type, wherein the first intermediate image is an SR image corresponding to the input image;
- applying SR interpolation to the input image to obtain a baseline image;
- and
- obtaining an output image based on the first intermediate image and the baseline image, which comprises:
- obtaining an intermediate output image based on the baseline image and the first intermediate image;
- obtaining a second intermediate image by applying the input image to an SR neural network;
- and obtaining the output image based on the second intermediate image and the intermediate output image.
A non-transitory computer-readable storage medium storing instructions that, when executed by a processor, cause the processor to perform a method for performing super-resolution (SR), wherein the method comprises:
- determining a direction type of an input image based on a gradient of the input image;
- obtaining a first intermediate image based on the direction type using a look-up table (LUT) that stores an SR operation result of a pixel value combination corresponding to a kernel set mapped to the determined direction type, wherein the first intermediate image is an SR image corresponding to the input image;
- applying SR interpolation to the input image to obtain a baseline image;
- and
- obtaining an output image based on the first intermediate image and the baseline image,
- wherein the determining of the direction type of the input image comprises:
- obtaining a differential element for each axis of the input image by applying a mask for a differential for each axis of the input image;
- and
- determining one of a plurality of preset direction types as the direction type of the input image based on an angle of a gradient of the input image obtained from the differential element for each axis of the input image.
An apparatus for super-resolution (SR) image processing, the apparatus comprising:
- at least one processor configured to:
- determine a direction type of an input image based on a gradient of the input image;
- obtain a first intermediate image based on the direction type using a look-up table (LUT) that stores an SR operation result of a pixel value combination corresponding to a kernel set mapped to the determined direction type, wherein the first intermediate image is an SR image corresponding to the input image;
- apply SR interpolation to the input image to obtain a baseline image;
- and
- obtain an output image based on the first intermediate image and the baseline image,
- wherein the at least one processor is configured to obtain the first intermediate image by:
- obtaining a second intermediate image by applying the input image to an SR neural network, wherein the first intermediate image is a corrected SR image corresponding to the second intermediate image, and wherein the LUT stores a SR correction result of the pixel value combination corresponding to the kernel set mapped to the determined direction type.
Dependencies are inferred from the claim text.