Color restoration method and apparatus
AssigneeLG Electronics Inc.
InventorsWoonchae Lee, Wonsu Choi, Seonhui Sunny Kim, Minho Lee
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Abstract
Disclosed herein is a color restoration method and apparatus. The color restoration method may include pre-processing an input image, determining whether color is distorted, and restoring the color of the input image in an RGB scale or a grayscale according to whether the color is distorted. According to the present disclosure, color of a low light image may be restored using a deep neural network model trained through deep learning of a 5G network and color restoration.
Claims14
A color restoration method performed by a color restoration apparatus, the color restoration method comprising:
- pre-processing an input image to generate a pre-processed input image;
- determining whether color of the pre-processed input image is distorted by using a detected reference image;
- and
- restoring the color of the pre-processed input image in an RGB scale or a grayscale according to whether the color is distorted,
- wherein the determining whether the color of the pre-processed input image is distorted comprises:
- detecting the reference image to be compared with the pre-processed input image;
- and
- determining whether the color of the pre-processed input image is distorted through color comparison between the pre-processed input image and the reference image,
- wherein the detecting the reference image comprises detecting, as the reference image, an image including an object displayed in a single color or an object including a specific color in common among objects displayed in the input image and having an RGB distribution most similar to an RGB distribution of the input image among candidate images based on an RGB distribution on a histogram of the input image, and
- wherein the restoring the color of the pre-processed input image in the grayscale comprises:
- converting the input image into a grayscale;
- and
- colorizing the grayscale image based on an RGB value of an input image before conversion.
A color restoration method performed by a color restoration apparatus, the color restoration method comprising:
- pre-processing an input image to generate a pre-processed input image;
- determining whether color of the pre-processed input image is distorted by using a detected reference image;
- and
- restoring the color of the pre-processed input image in an RGB scale or a grayscale according to whether the color is distorted,
- wherein the determining whether the color of the pre-processed input image is distorted comprises:
- detecting the reference image to be compared with the pre-processed input image;
- and
- determining whether the color of the pre-processed input image is distorted through color comparison between the pre-processed input image and the reference image,
- wherein the detecting the reference image comprises detecting, as the reference image, an image having an RGB distribution most similar to an RGB distribution of the input image among candidate images based on an RGB distribution on a histogram of the input image.
A color restoration apparatus comprising:
- a processor configured to pre-process an input image to generate a pre-processed input image;
- and
- a deep neural network (DNN) model configured to restore distorted color of the pre-processed input image in an RGB scale or a grayscale,
- wherein the processor determines whether color of the pre-processed input image is distorted by using a detected reference image, and detects as the reference image, an image including an object displayed in a single color or an object including a specific color in common among objects displayed in the input image, and having an RGB distribution most similar to an RGB distribution of the input image among candidate images based on an RGB distribution on a histogram of the input image, and determines whether the color of the pre-processed input image is distorted through color comparison between the pre-processed input image and the reference image, and
- wherein the processor controls the DNN to convert the input image into a grayscale, and to colorize the grayscale image based on an RGB value of an input image before conversion.
Dependencies are inferred from the claim text.