ID 原文 译文
2183 针对当前内容感知的重定向方法中可能出现的变形和失真问题，提出一种融合显著与深度信息的缝切割重定向方法。 To solve the problem of deformation and distortion that may occur in the current content-aware redirection method, a retargeting method with seam-carving combining saliency and depth information is proposed.
2184 首先利用 GBVS 算法获取图像显著信息，结合图像梯度信息与通过 SIFT 匹配方法获取的图像深度信息构建更精确的重要度图; Specifically, the GB-VS algorithm is used to obtain the saliency information, and the image gradient information is combined with the image depth information acquired by the SIFT matching method to construct a more accurate importance map.
2185 其次，根据重要度图的能量分布，对原始图像进行处理，得到最终的重定向结果。 Then, according to the energy distribution of the importance map, the original image is processed to obtain the final results.
2186 基于公开数据库在两个不同评价标准下与多种重定向方法的对比表明，本文方法能够最大程度的保留图像的显著部分。 The comparison onthe public database with different methods under two evaluation criteria shows that the proposed method can preserve the sig-nificant part of the image to the greatest extent.
2187 导向滤波算法是一种有效的基于边保持的平滑滤波算法。 Guided image filtering is an effective edge-preserving smoothing technique.
2188 然而，由于算法中的正则化系数和细节层增益是固定的，可能会导致边附近出现光晕以及背景中出现大量噪声，降低图像的质量。 However, because the regulari-zation parameter and amplification factor of the detail layer are fixed instead of content adaptive, the halo effects near the ed-ges and noise in the background may be incurred, which will degrade the quality of the output images further.
2189 在本文中，首先给出了一种改进的基于边的权重系数计算方法，它能够较准确地实现边保持，减少光晕现象。 In this paper, an improved edge-aware weighting is first proposed to preserve the edges more accurately and reduce the halo effects.
2190 其次，提出了基于梯度导向的细节层增益计算方法，可以有效地增强细节并且抑制噪声。 Then, the amplification factor of the detail layer is calculated in a gradient-directed way for boosting the details while suppressing the noise.
2191 实验表明，对于含有大量噪声和小细节的低剂量 CT 图像，本文方法可以减少噪声和光晕的影响，显著提高图像的对比度，满足临床诊断的需要。 Experimental results on the low-dose CT images with heavy noise and small details show that the proposed methodcan reduce the halo effects and attenuate the noise while enhancing the contrast efficiently. The visual quality of the outputimages meets the requirement of the clinical diagnosis.
2192 针对目前入侵检测效率不高的问题，本文提出一种基于感知哈希矩阵的最近邻入侵检测算法。 In view of the low efficiency of current intrusion detection, this paper proposes a Nearest Neighbor Intru-sion Detection algorithm based on Perceptual Hash Matrix.