哪种超分辨率算法适合波斯语文本图像序列

Elham Khodadadi, H. Kanan
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引用次数: 0

摘要

本文提出了一种新的波斯语文本图像序列超分辨算法。我们的算法包含三个主要步骤作为先验的超分辨率算法;注册、重建和恢复。由于波斯语文本的特殊性质,如字母中出现点,选择合适的超分辨率算法,特别是在存在噪声的情况下,就显得尤为重要。我们提出了一种精确的亚像素配准和IBP重建算法,该算法可以从一组低分辨率噪声观测数据中重建出高分辨率图像。在恢复步骤中,我们利用NLM算法来克服图像噪声。我们在合成数据和真实数据上测试了我们的算法。定量和定性结果均表明了算法的优越性。
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Which super-resolution algorithm is proper for Farsi text image sequences
In this paper we propose a new algorithm for super-resolution of Farsi text image sequences. Our algorithm contains three main steps as prior super-resolution algorithms; registration, reconstruction, and restoration. Due to special properties of Farsi texts such as appearance of dots in alphabet, selecting a proper super-resolution algorithm, especially in presence of noise, is more important. We propose an algorithm with an accurate sub-pixel registration and IBP reconstruction that reconstructs a high resolution image from a set of noisy low resolution observations. In restoration step we have exploited NLM algorithm to overcome image noise. We test our algorithm on synthetic and real data. Both quantitative and qualitative results show outperformance of our algorithm.
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