کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6866550 | 679631 | 2014 | 15 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Super-resolution for facial image using multilateral affinity function
ترجمه فارسی عنوان
وضوح فوق العاده برای تصویر چهره با استفاده از تابع وابستگی چند جانبه
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کلمات کلیدی
توهم چهره، فوق العاده رزولوشن، تابع وابستگی، رگرسیون کاسو،
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
هوش مصنوعی
چکیده انگلیسی
In this paper, a patch-based super-resolution (SR) method is proposed to hallucinate facial images, where the image patches are selected and weighted based on a multilateral affinity function (MAF). Inspired by the property of human faces, we design the MAF by combining four parts, each of which is also an affinity function and inspired from different insights. The first part describes the similarity of two patches by their appearances. The second one takes the probable positions of patches into account. The third part incorporates the global information of faces by Lasso regression. The fourth one includes the information of significant facial components. Through the data consistency constraint, weights of training patches are calculated from MAF. The final SR results are obtained by the stitching of inferred HR patches and a post-processing. The experiments on two public databases demonstrate the superiority of the proposed method over some state-of-the-art methods via various criteria. The feasibility of our method in the real-world scenario is also demonstrated experimentally.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Neurocomputing - Volume 133, 10 June 2014, Pages 194-208
Journal: Neurocomputing - Volume 133, 10 June 2014, Pages 194-208
نویسندگان
Fei Zhou, Biao Wang, Qingmin Liao,