کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
4972918 1451245 2017 11 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Poor textural image tie point matching via graph theory
ترجمه فارسی عنوان
تطبیق نقاط بافت نقاشی تطبیق از طریق نظریه گراف
کلمات کلیدی
تیک تیک نقطه تصویر بافت ضعیف، تانسور وابستگی، لبه وزن، تطبیق گراف بالاترین مرتبه،
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر سیستم های اطلاعاتی
چکیده انگلیسی
Feature matching aims to find corresponding points to serve as tie points between images. Robust matching is still a challenging task when input images are characterized by low contrast or contain repetitive patterns, occlusions, or homogeneous textures. In this paper, a novel feature matching algorithm based on graph theory is proposed. This algorithm integrates both geometric and radiometric constraints into an edge-weighted (EW) affinity tensor. Tie points are then obtained by high-order graph matching. Four pairs of poor textural images covering forests, deserts, bare lands, and urban areas are tested. For comparison, three state-of-the-art matching techniques, namely, scale-invariant feature transform (SIFT), speeded up robust features (SURF), and features from accelerated segment test (FAST), are also used. The experimental results show that the matching recall obtained by SIFT, SURF, and FAST varies from 0 to 35% in different types of poor textures. However, through the integration of both geometry and radiometry and the EW strategy, the recall obtained by the proposed algorithm is better than 50% in all four image pairs. The better matching recall improves the number of correct matches, dispersion, and positional accuracy.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: ISPRS Journal of Photogrammetry and Remote Sensing - Volume 129, July 2017, Pages 21-31
نویسندگان
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