کد مقاله کد نشریه سال انتشار مقاله انگلیسی ترجمه فارسی نسخه تمام متن
4944112 1363983 2018 12 صفحه PDF ندارد دانلود رایگان
عنوان انگلیسی مقاله
Local and global sparse representation for no-reference quality assessment of stereoscopic images
ترجمه فارسی عنوان
بازنمایی پراکنده محلی و جهانی برای ارزیابی کیفیت بدون مرجع تصاویر استریو اسکوپیک
کلمات کلیدی
تصویر 3D استریوسکوپیک؛ ارزیابی کیفیت بدون مرجع ؛ بازنمایی پراکنده چندمودال؛
Stereoscopic 3D image; No-reference quality assessment; Multi-modal sparse representation;
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
چکیده انگلیسی

No-reference/blind quality assessment of stereoscopic 3D images is much more challenging than 2D images due to the poor understanding of binocular vision. In this paper, we propose a BLind Quality Evaluator for stereoscopic 3D images by learning Local and Global Sparse Representations (BLQELGSR). Specifically, at the training stage, we first construct a large-scale training set by simulating some common distortions that are likely encountered by stereoscopic images, and propose a multi-modal sparse representation framework to characterize the relationship between the feature and quality spaces for all sources of information from left, right and cyclopean views in local and global manners. At the testing stage, based on the derived 3D quality prediction framework, the local and global quality scores from different sources are predicted and combined to drive a final 3D quality score. Experimental results on three 3D image quality databases show that in comparison with the existing methods, the devised BLQELGSR can achieve better prediction performance to be in line with subjective assessment.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Information Sciences - Volume 422, January 2018, Pages 110-121
نویسندگان
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