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

机译:一种新的基于局部边缘轮廓保存的去噪算法的性能评估

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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:在保留清晰细节和精细边缘的同时对数字图像进行降噪是研究的活跃领域。本文提出了一种在零均值高斯噪声的情况下针对数字图像的基于局部边缘轮廓检测和保存的新型降噪算法。检测并保留图像像素强度的急剧变化可以保留去噪图像的视觉质量。在图片的3×3重叠图块中检测到二十四种不同类型的边缘和方向。根据边缘的类型和方向,每个图块都将沿着检测到的边缘方向进行整合。这样可以保留边缘。如果图块没有任何边缘,则进行简单的平均。通过获取相同边缘的重叠图块并在边缘方向上合并两个相邻图块,可以保持边缘的连续性。避免跨边缘的整合以保持边缘的清晰度。根据新颖的边缘表示参数,即输入图像中的边缘瓦片的数量,所提出的算法与其他去噪算法进行了基准测试。所提出的算法明显优于其他当代算法。在去噪过程中,大多数其他算法要么过度构造边缘,要么构造不足边缘。

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