发明名称 Image sharpness classification system
摘要 A method for predicting whether a test image (318) is sharp or blurred includes the steps of: training a sharpness classifier (316) to discriminate between sharp and blurred images, the sharpness classifier (316) being trained based on a set of training sharpness features (314) computed from a plurality of training images (306), the set of training sharpness features (314) for each training image (306) being computed by (i) resizing each training image (306) by a first resizing factor; (ii) identifying texture regions (408, 410) in the resized training image; and (iii) computing the set of sharpness features in the training image (412) from the identified texture regions; and applying the trained sharpness classifier (316) to the test image (318) to determine if the test image (318) is sharp or blurred based on a set of test sharpness features (322) computed from the test image (318), the set of test sharpness features (322) for each test image (318) being computed by (i) resizing the test image (318) by a second resizing factor that is different than the first resizing factor; (ii) identifying texture regions (408, 410) in the resized test image; and (iii) computing the set of sharpness features in the test image (412) from the identified texture regions.
申请公布号 US9251439(B2) 申请公布日期 2016.02.02
申请号 US201114118966 申请日期 2011.08.18
申请人 NIKON CORPORATION 发明人 Hong Li
分类号 H04N5/232;H04N5/217;G06K9/66;G06K9/62;G06K9/46;G06K9/52;G06K9/40;G06K9/03;G06T7/00 主分类号 H04N5/232
代理机构 Roeder & Broder LLP 代理人 Roeder & Broder LLP
主权项 1. A method for determining if a test image is either sharp or blurred, the method comprising the steps of: training a sharpness classifier to discriminate between sharp and blurred images, the sharpness classifier being trained based on a set of training sharpness features computed from a plurality of training images, the set of training sharpness features for each training image being computed by (i) resizing each training image by a first resizing factor; (ii) identifying texture regions in the resized training image; and (iii) computing the set of sharpness features in the training image from the identified texture regions; and applying the trained sharpness classifier to the test image to determine if the test image is sharp or blurred based on a set of test sharpness features computed from the test image, the set of test sharpness features for each test image being computed by (i) resizing the test image by a second resizing factor that is different than the first resizing factor; (ii) identifying texture regions in the resized test image; and (iii) computing the set of sharpness features in the test image from the identified texture regions.
地址 Tokyo JP