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Titlebook: Computer Vision; Second CCF Chinese C Jinfeng Yang,Qinghua Hu,Deyu Meng Conference proceedings 2017 Springer Nature Singapore Pte Ltd. 2017

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Communications in Computer and Information Sciencehttp://image.papertrans.cn/c/image/233994.jpg
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Dust Image Enhancement Algorithm Based on Color Transferental results show that our algorithm can effectively enhance dust images quality in different degree, get more image details and resolve the definition and hue correction problems. We proposed a absolute color difference index to measure this method. The experiments demonstrate that the proposed al
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1865-0929 bject detection and classification; object identification; photography and video; robot vision; shape representation and matching; statistical methods and learning; video analysis and event recognition; visual salient detection..978-981-10-7298-7978-981-10-7299-4Series ISSN 1865-0929 Series E-ISSN 1865-0937
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https://doi.org/10.1007/978-1-4757-4321-04 is applied to adjust the passed windows at last and the adjusted windows are regarded as final positions. The experimental results show that our method can achieve real time detection at the rate of 14FPS and be robust with a small size of training data. The detection accuracy is much higher than
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https://doi.org/10.1007/978-3-658-19784-1t procedure. Besides, a model update scheme via particle filter is developed to capture the appearance variations. Our framework allows the modalities to be original pixels or other extracted features from single image or different spectral images, and provides the flexibility to arbitrarily add or
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