首页> 外文会议>AICI 2011;International conference on artificial intelligence and computational intelligence >Denoising of Coal Flotation Froth Image Using Opening and Closing Filters with Area Reconstruction and Alternating Order Filtering
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Denoising of Coal Flotation Froth Image Using Opening and Closing Filters with Area Reconstruction and Alternating Order Filtering

机译:使用带区域重构和交替阶滤波的开闭滤波器对煤浮选泡沫图像进行去噪

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Image denoising of coal flotation froth plays an important part in the subsequent image processing such as image segmentation and feature extraction. In traditional image denoising, there exists some inconsistency between removing the noise and preserving the most sharp detail information of object edges. In this paper, a morphological denoising algorithm is proposed for removing the noise of coal flotation froth image. This algorithm combines the opening and closing filters based on area reconstruction with an alternating order filtering method, and the elliptical structuring elements with increasing radius are adopted in the morphological filters. Based on the algorithm, denoise processing of a lot of coal froth images acquired from coal flotation working site was carried out. Denoising results show that many isolated spots on the original bubble images have been obviously eliminated, and no edge blurring appears, instead, the useful detail information in image is preserved.
机译:煤浮选泡沫的图像去噪在图像分割和特征提取等后续图像处理中起着重要的作用。在传统的图像去噪中,在去除噪声与保留对象边缘最清晰的细节信息之间存在一些不一致之处。提出了一种形态学去噪算法,用于去除浮选泡沫图像的噪声。该算法结合了基于面积重构的开闭滤波器和交替阶滤波方法,并在形态滤波器中采用了半径增大的椭圆结构元素。基于该算法,对浮选工作现场采集的大量煤泡沫图像进行了降噪处理。去噪结果表明,原始气泡图像上的许多孤立斑点已被明显消除,并且没有出现边缘模糊,而是保留了图像中有用的细节信息。

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