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Matlab在激光水下图像处理中的应用
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科技导报 |研究论文 2010 , 28 (10) : 87 -89
Matlab在激光水下图像处理中的应用
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蒋洁,焦斌亮
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    燕山大学信息科学与工程学院,河北秦皇岛 066004
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蒋洁
Underwater Laser Image Processing with Matlab
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    出版时间: 2010-05-28
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    水下激光成像技术在水下探测等海洋开发中具有重要的实用价值,但水介质的特殊性,使其所成图像易受噪声污染而造成分辨率下降。即使采用同步扫描和距离选通等技术,获得的成像质量仍然不好,图像存在由后向散射形成的散斑噪声和其他一些高斯噪声。为了进一步改善成像效果,需要利用数字图像处理技术对水下成像进行后续加工,水下图像处理结果的好坏直接影响到后面的特征提取和目标识别等的成败。本文分析了Matlab在数字图像处理中的应用, 并结合对激光水下图像的处理,说明了Matlab在图像处理中的强大功能,对常用的噪声抑制算法:维纳滤波、中值滤波、均值滤波进行了介绍,并且通过对实际的激光水下图像处理,利用以上各算法计算了处理图像的散斑指数、峰值信噪比和归一化均方误差,比较了其散斑抑制能力。
    散斑噪声  /  滤波算法  /  图像处理  /  Matlab软件
    The underwater laser imaging is very important for ocean exploitation, but its image is usually affected by speckle noise in water. Although synchronous scanning technology and range-gated technology are mostly applied, perfect processing results still can not be guaranteed. Background noises enter the underwater laser images due to light absorption and scattering in water, which is responsible for the low contrast of the underwater images. In order to improve the images, digital image processing techniques are used. This paper discusses the functions of Matlab and their applications in digital image processing, and the powerful ability of Matlab is shown in underwater laser image processing. Three common algorithms-Wiener filtering, median filtering, mean filtering were compared in terms of the speckle indexes, peak signal to noise ratio and normalized mean square error of the processed images.
    speckle noise  /  filtering algorithm  /  image processing  /  Matlab software
    蒋洁;焦斌亮. Matlab在激光水下图像处理中的应用. 科技导报, 2010 , 28 (10) : 87 -89 .
    . Underwater Laser Image Processing with Matlab[J]. Science & Technology Review, 2010 , 28 (10) : 87 -89 .

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    鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
    小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
    多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
    红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
    小菇属 Mycena 11 5.26
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