公开(公告)号：US20230147540A1

公开(公告)日：2023-05-11

申请号：US18149903

申请日：2023-01-04

Applicant: Samsung Electronics Co., Ltd.

Inventor： Kwangyong LIM ,  Sungoh KIM ,  Soohyeong LEE

IPC: G06T7/00 ,  G06V10/74 ,  G06F3/14

CPC classification number: G06T7/0002 ,  G06V10/761 ,  G06F3/14 ,  G06T2207/30168

Abstract: An electronic device is provided. The electronic device includes memory for storing at least one image, a display, and at least one processor electrically connected with the memory and display, and the at least one processor may obtain a request related to a quality of a first image among the at least one image, in response to the request, determine whether detecting a plurality of degradations of the first image is completed before obtaining the request, as a result of determining, if detecting the plurality of the degradations is not completed, determine whether a degradation improvement condition is satisfied for the first image, detect the plurality of the degradations in response to satisfying the degradation improvement condition, determine whether a criterion for improving the plurality of the degradations is satisfied, in response to satisfying the criterion, display on the display a second image in which degradation improvement is performed.

公开(公告)号：US20250037248A1

公开(公告)日：2025-01-30

申请号：US18911012

申请日：2024-10-09

Applicant: SAMSUNG ELECTRONICS CO., LTD.

Inventor： Siddharth Deepak ROHEDA ,  Amit Satish UNDE ,  Alok Shankarlal SHUKLA ,  Rishikesh JHA ,  Soohyeong LEE ,  Shashavali DOODEKULA ,  Sai Kumar Reddy MANNE ,  Saikat Kumar DAS

IPC: G06T5/73

Abstract: A method of detecting blur in an input image, the method including: detecting one or more candidate blur regions of a plurality of regions in the input image; determining, a first confidence score of the one or more candidate blur regions in the input image; determining a second confidence score of a global blur in the input image; determining a third confidence score of an intentional blur in the input image; and detecting a type of blur and a strength of the type of blur in the input image based on the first confidence score of the one or more candidate blur regions, the second confidence score of the global blur, and the third confidence score of the intentional blur.