کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
537177 870765 2016 14 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Single image super resolution using local smoothness and nonlocal self-similarity priors
ترجمه فارسی عنوان
رزولوشن فوق العاده تصویر با استفاده از روش صحیح محلی و غیرقابل انعطاف پذیری غیرفعال
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر چشم انداز کامپیوتر و تشخیص الگو
چکیده انگلیسی


• A reconstruction-based single image super resolution method is presented.
• Local smoothness and nonlocal self-similarity priors are incorporated in our model.
• The Split Bregman Iteration is imitated to solve the L1-regularized problem.
• The proposed method can achieve higher quality results.

Single image super resolution (SISR) is an inverse problem, so an effective image prior is necessary to reconstruct a high resolution (HR) image from a single low resolution (LR) image. On the one hand, natural images satisfy the property of local smoothness; on the other hand, the patches could find some similar patches in different locations within the same image, and this property is known as nonlocal self-similarity. In this paper, we propose a SISR method by incorporating the local smoothness and nonlocal self-similarity priors in the reconstruction-based SISR framework simultaneously, and the Split Bregman Iteration (SBI) optimization algorithm is imitated to solve the L1-regularized problem. Experimental results show that, in most case, the proposed method quantitatively and qualitatively outperforms the state-of-the-art SISR algorithms.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Signal Processing: Image Communication - Volume 43, April 2016, Pages 68–81
نویسندگان
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