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Classification of hazy and non-hazy images

机译:朦胧和非朦胧图像的分类

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摘要

For defogging of pictures, initially it is investigated that if the picture is foggy or clear and for this someone cannot depend upon view of human, so for deciding the picture state as foggy or clear must be comprehended first. In this proposed work, 19 classification techniques are applied to judge whether a picture is foggy or clear. Based on characteristic difference of foggy and clear pictures, the five parameters which are area, mean, min intensity, max intensity, standard deviation are used for training the classification system. Some of the classification techniques provide very good accuracy and can be used further in defogging algorithms in basic step of image state recognition.
机译:对于图像的除雾,首先要研究的是,如果图像有雾或清晰,并且为此,某人不能依赖于人的视野,因此必须首先理解将图像状态确定为有雾或清晰。在这项拟议的工作中,应用了19种分类技术来判断图片是否模糊或清晰。根据有雾和清晰图片的特征差异,使用面积,平均值,最小强度,最大强度,标准差这五个参数来训练分类系统。一些分类技术提供了非常好的准确性,并且可以在图像状态识别的基本步骤中进一步用于除雾算法中。

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