Invention Grant
- Patent Title: Joint blur map estimation and blur desirability classification from an image
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Application No.: US15989436Application Date: 2018-05-25
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Publication No.: US10776671B2Publication Date: 2020-09-15
- Inventor: Zhe Lin , Xiaohui Shen , Shanghang Zhang , Radomir Mech
- Applicant: Adobe Inc.
- Applicant Address: US CA San Jose
- Assignee: Adobe Inc.
- Current Assignee: Adobe Inc.
- Current Assignee Address: US CA San Jose
- Agency: Finch & Maloney PLLC
- Main IPC: G06K9/62
- IPC: G06K9/62 ; G06K9/46 ; G06T7/00 ; G06N3/08

Abstract:
Techniques are disclosed for blur classification. The techniques utilize an image content feature map, a blur map, and an attention map, thereby combining low-level blur estimation with a high-level understanding of important image content in order to perform blur classification. The techniques allow for programmatically determining if blur exists in an image, and determining what type of blur it is (e.g., high blur, low blur, middle or neutral blur, or no blur). According to one example embodiment, if blur is detected, an estimate of spatially-varying blur amounts is performed and blur desirability is categorized in terms of image quality.
Public/Granted literature
- US20190362199A1 JOINT BLUR MAP ESTIMATION AND BLUR DESIRABILITY CLASSIFICATION FROM AN IMAGE Public/Granted day:2019-11-28
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