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Indrawing on the Picture Edge Based on Wavelet Technology

机译:基于小波技术的画面探开

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Have studied the wave technology'sapplication in drawing on the picture edge, the local segmentation problem preliminarily solved existing in the picture. The traditional chain-length concept is discarded and the percentage concept of the chain is proposed. The edge-growth method is adopted to get the good closed image. The edges checked by wavelet transforms are of single pixel and accurate orientation and wavelet transform on every image scale can see some edge information. An evident method is to integrate all edge images with all scales in an attempt to play their different advantages to gain accurate edge with wide single pixel. Based on peculiarities of wavelet transform, we can adopt a special general arithmetic to obtain image edge with wide single pixel. Taking advantage of wavelet transform technology, we can not only avoid some trivial and uncertainty brought by setting gray threshold but also wavelet has anti-noise function and is able to capture image details. Most importantly, wavelet can be usable in all images with various gray levels. Firstly, we use designed adaptive filter to filter the waves and then transform wavelet for three times, so we can see wave filter maintain edge while getting rid of noises, Lastly the image segmentation is implemented by finding large regions.
机译:已经研究了在画面上绘制的波技术的应用,局部分割问题在图片中初步解决。传统的链长概念被丢弃,提出了链条的百分比概念。采用边缘增长方法来获得良好的封闭图像。通过小波变换检查的边缘是单像素的单像素和精确的方向和小波变换,每个图像刻度都可以看到一些边缘信息。显而易见的方法是将所有边缘图像集成到所有尺度中,以尝试使用不同的优点来获得具有宽单像素的准确边缘。基于小波变换的特殊性,我们可以采用特殊的一般算法,以获得具有宽单像素的图像边缘。利用小波变换技术,我们不仅可以避免通过设置灰度阈值而带来的一些琐碎和不确定性,而且小波具有抗噪声功能,并且能够捕获图像细节。最重要的是,小波可以可以使用各种灰度级的所有图像中。首先,我们使用设计的自适应滤波器来过滤波浪,然后将小波变换为三次,因此我们可以看到波过滤器保持边缘,同时摆脱噪声,最后通过查找大区域来实现图像分割。

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