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Denoise in the Pool Alarm System Based on Wavelet Transform

机译:基于小波变换的水池报警系统消噪

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A method operating at an outdoor swimming pool is presented in this paper. In a swimming pool, one key problem we faced is that the SNR (signal to noise ratio) will be lower than general surroundings such as bubbles, shadow, water waves, and lower contrast. In order to eliminate noise and preserve the edge and texture detail in the image that we obtained, we select the wavelet denoising algorithm. Because the contrast is lower and the wavelet transform will make the image fuzzy, firstly, we use the canny edge detection operator to detect the feature of the image. generally, water waves are in the special location for the swimming pool, we ignore the water waves edge information. Secondly, we use wavelet transform to process the processed edge image and the original image, then we add these wavelet coefficients at the corresponding level, we will reserve the first level wavelet transform coefficients. Finally, we can use the Donoho hard threshold denoise technology to eliminate the noise. For our actual situation, our algorithm makes some improvement in two aspects. The experiment shows that image denoise perform better than that using traditional method
机译:本文提出了一种在室外游泳池工作的方法。在游泳池中,我们面临的一个关键问题是SNR(信噪比)将低于气泡,阴影,水波和较低对比度等一般环境。为了消除噪声并保留所获得图像中的边缘和纹理细节,我们选择了小波去噪算法。由于对比度较低,并且小波变换会使图像模糊,因此,首先,我们使用Canny边缘检测算子来检测图像的特征。通常,水波位于游泳池的特殊位置,因此我们忽略了水波边缘信息。其次,我们使用小波变换来处理经过处理的边缘图像和原始图像,然后在相应的级别上添加这些小波系数,我们将保留第一级小波变换系数。最后,我们可以使用Donoho硬阈值降噪技术消除噪声。针对我们的实际情况,我们的算法在两个方面做了一些改进。实验表明,图像去噪性能优于传统方法。

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