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Performance evaluation of a new local edge profile preservation based denoising algorithm

机译:基于新的局部边缘剖面保存的绩效评估

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Denoising digital images while preserving sharp details and fine edges is an active area of research. This paper presents novel local edge profile detection and preservation based denoising algorithm for digital images in presence of zero mean Gaussian noise. Detecting and preserving sharp changes in image pixel intensities preserves the visual quality of the denoised image. Twenty four different types and orientations of edges are detected in 3×3 overlapping tiles of a picture. Based on the edge type and orientation, each tile is subjected to integration along the direction of the detected edge. This preserves the edges. Simple averaging is done if a tile does not have any edge. Continuity of edges is maintained by taking the overlapping tiles of the same edge and integrating both the neighbouring tiles in the direction of the edge. The integration across the edges are avoided to preserve the sharpness of the edges. The proposed algorithm is benchmarked with other denoising algorithms in terms of a novel edge representation parameter i.e. number of edge tiles in the input image. The proposed algorithm clearly outperforms the other contemporary algorithms. Most of the other algorithms either over construct or under construct the edges during denoising.
机译:在保持尖锐的细节和精细边缘的同时去噪是一个活跃的研究领域。本文介绍了零均匀高斯噪声存在的数字图像的新型局部边缘轮廓检测和保存的去噪算法。检测和保留图像像素强度的急剧性变化,保留了去噪图像的视觉质量。在图像的3×3重叠瓦片中检测到二十四种不同类型和边缘方向。基于边缘类型和方向,每个瓦片沿着检测到的边缘的方向进行集成。这保留了边缘。如果瓦片没有任何边缘,则完成简单的平均。通过拍摄相同边缘的重叠瓦片并在边缘的方向上积分相邻瓦片来保持边缘的连续性。避免了跨越边缘的集成以保持边缘的锐度。所提出的算法在新颖的边缘表示参数中与其他去噪算法基准测试。输入图像中的边缘瓦片数量。该算法显然优于其他当代算法。大多数其他算法在构建过程中或在去噪期间构造边缘。

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