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Onvif设备搜索 示例源码

SIFT，即尺度不变特征变换（Scale-invariant feature transform，SIFT），是用于图像处理领域的一种描述。这种描述具有尺度不变性，可在图像中检测出关键点，是一种局部特征描述子。[1] 该方法于1999年由David Lowe[2] 首先发表于计算机视觉国际会议（International Conference on Computer Vision，ICCV），2004年再次经David Lowe整理完善后发表于International journal of computer vision（IJCV）。截止2014年8月，该论文单篇被引次数达25000余次。(SIFT, namely Scale Invariant Feature Transform (Scale-invariant feature transform, SIFT), it is a description for image processing. This description has scale invariance, can detect critical point in the image, it is a local feature descriptor. [1] The method in 1999 by David Lowe [2] First published in the International Conference on Computer Vision (International Conference on Computer Vision, ICCV), 2004 was again perfect finishing after David Lowe published in the International journal of computer vision (IJCV) . As of August 2014, the paper cited the number of times a single article of more than 25,000 times.)

用于计算两幅图片之间的峰值信噪比，从而衡量图片重建质量(It used to calculate the peak signal to noise ratio between the two pictures, which measure the quality of the reconstructed image)

对脉搏波的波峰波谷以及重搏波拐点的检测，挺好用的。。(On the pulse wave dicrotic wave peaks and valleys as well as the inflection point detection, very good use. .)

说明：  经典的粒子滤波算法，适用于粒子滤波的初学者更好的了解粒子滤波(Classical particle filter, particle filter for better understanding of particle filter for beginners)

本代码主要给出了激光粒度仪颗粒散射光强分布以及4种粒度反演算法，以及4种算法之间的比较。四种反演算法为：TSVD、Chaine、Tikhonov和l1正则化。(The code gives the Zetasizer particle scattering intensity distribution, and four kinds of particle inversion algorithm, as well as a comparison between the four algorithms. Four kinds of inversion algorithm is: TSVD, Chaine, Tikhonov and l1 regularization.)

此文件是关于图像处理中灰度视频播放等相关知识的综合运用。(it is about the gray in image processing)

运用Soble,,Roberts算子,Prewitt算子,Log算子,Canny算子j进行边缘检测 (Using Sobel ,, Roberts operator, Prewitt operator, Log operator, Canny edge detection operator )

说明：  图像的尺度不变特征特征点提取，快速提取图像的特征点(SIFT feature extraction of image)

图像从背景图中提取 可以用来提取边缘，将背景图与图像分离(Images extracted from the background image can be used to extract the edge of the background map and image separation)