1. Gray-Scale Image Dehazing Guided by Scene Depth Information
- Author
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Bo Jiang, Zhang Wanxu, Min Liu, Yi Ru, Hongqi Meng, Xiaolei Ma, Jian Zhao, and Chen Xiaoxuan
- Subjects
Article Subject ,Computer science ,Image quality ,General Mathematics ,ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION ,Image processing ,02 engineering and technology ,Grayscale ,Composite image filter ,Image texture ,Distortion ,0202 electrical engineering, electronic engineering, information engineering ,Computer vision ,Image warping ,Image restoration ,Feature detection (computer vision) ,business.industry ,Color image ,lcsh:Mathematics ,Binary image ,020208 electrical & electronic engineering ,General Engineering ,Pattern recognition ,lcsh:QA1-939 ,lcsh:TA1-2040 ,020201 artificial intelligence & image processing ,Artificial intelligence ,lcsh:Engineering (General). Civil engineering (General) ,business - Abstract
Combined with two different types of image dehazing strategies based on image enhancement and atmospheric physical model, respectively, a novel method for gray-scale image dehazing is proposed in this paper. For image-enhancement-based strategy, the characteristics of its simplicity, effectiveness, and no color distortion are preserved, and the common guided image filter is modified to match the application of image enhancement. Through wavelet decomposition, the high frequency boundary of original image is preserved in advance. Moreover, the process of image dehazing can be guided by the image of scene depth proportion directly estimated from the original gray-scale image. Our method has the advantages of brightness consistency and no distortion over the state-of-the-art methods based on atmospheric physical model. Particularly, our method overcomes the essential shortcoming of the abovementioned methods that are mainly working for color image. Meanwhile, an image of scene depth proportion is acquired as a byproduct of image dehazing.
- Published
- 2016