View source for 18241637. METHOD AND DEVICE FOR CORRECTING IMAGE ON BASIS OF COMPRESSION QUALITY OF IMAGE IN ELECTRONIC DEVICE simplified abstract (SAMSUNG ELECTRONICS CO., LTD.)

=METHOD AND DEVICE FOR CORRECTING IMAGE ON BASIS OF COMPRESSION QUALITY OF IMAGE IN ELECTRONIC DEVICE=


==Organization Name==

[[:Category:SAMSUNG ELECTRONICS CO., LTD.|SAMSUNG ELECTRONICS CO., LTD.]]


[[Category:SAMSUNG ELECTRONICS CO., LTD.]]

==Inventor(s)==

[[:Category:Kyuwon Kim of Suwon-si (KR)|Kyuwon Kim of Suwon-si (KR)]][[Category:Kyuwon Kim of Suwon-si (KR)]]

[[:Category:Jongkyu Kim of Suwon-si (KR)|Jongkyu Kim of Suwon-si (KR)]][[Category:Jongkyu Kim of Suwon-si (KR)]]

[[:Category:Hyunsoo Kim of Suwon-si (KR)|Hyunsoo Kim of Suwon-si (KR)]][[Category:Hyunsoo Kim of Suwon-si (KR)]]

[[:Category:Sujung Bae of Suwon-si (KR)|Sujung Bae of Suwon-si (KR)]][[Category:Sujung Bae of Suwon-si (KR)]]

[[:Category:Heekuk Lee of Suwon-si (KR)|Heekuk Lee of Suwon-si (KR)]][[Category:Heekuk Lee of Suwon-si (KR)]]

[[:Category:Inho Choi of Suwon-si (KR)|Inho Choi of Suwon-si (KR)]][[Category:Inho Choi of Suwon-si (KR)]]

==METHOD AND DEVICE FOR CORRECTING IMAGE ON BASIS OF COMPRESSION QUALITY OF IMAGE IN ELECTRONIC DEVICE - A simplified explanation of the abstract==


This abstract first appeared for US patent application 18241637 titled 'METHOD AND DEVICE FOR CORRECTING IMAGE ON BASIS OF COMPRESSION QUALITY OF IMAGE IN ELECTRONIC DEVICE

==Simplified Explanation==

The patent application describes a method and system for classifying the quality of a compressed image and removing compression artifacts using a trained noise removal model. Here are the key points:

* The technology classifies the compression quality of an image and removes compression artifacts using a noise removal model.
* An electronic device with a display, memory, and processor is used to implement this technology.
* The processor selects a noise removal model based on the determined compression quality.
* The corrected image, with the compression artifact removed, is displayed for user feedback.
* The user has the option to confirm or reject the correction.

== Potential Applications ==
This technology has potential applications in various fields, including:

* Image editing software: It can be integrated into image editing software to automatically remove compression artifacts and enhance the quality of compressed images.
* Online image platforms: Online platforms that host and display images can use this technology to improve the visual quality of uploaded images.
* Video streaming services: Video streaming platforms can utilize this technology to enhance the quality of compressed video frames and reduce compression artifacts.

== Problems Solved ==
This technology addresses the following problems:

* Compression artifacts: Compressed images often suffer from compression artifacts, which degrade the visual quality. This technology removes these artifacts, improving the overall image quality.
* Manual correction: Previously, removing compression artifacts required manual editing, which was time-consuming and required expertise. This technology automates the process, saving time and effort.

== Benefits ==
The use of this technology offers several benefits:

* Improved image quality: By removing compression artifacts, the technology enhances the visual quality of compressed images, making them more appealing and usable.
* Time-saving: The automated removal of compression artifacts eliminates the need for manual editing, saving time and effort for users.
* User feedback: The ability for users to confirm or reject the correction allows for customization and ensures user satisfaction.


==Original Abstract Submitted==

A compression quality of a compression image is classified and a compression artifact of the compression image is removed on the basis of a noise removal model trained to correspond to the compression quality. The image with the artifact removed is a corrected image. An electronic device includes a display, a memory, and a processor. The processor selects a noise removal model trained to correspond to the determined compression quality and displays the corrected image for user feedback. The user may confirm or reject the correction.



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