Guohao Lyu

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With the rapid development of high-speed railway, the safety of railway becomes extremely important. Video is a direct and effective manner for monitoring railway environment, but it is easily affected by weather condition and ambient light. Therefore the security risks are hidden in the low light condition and difficult to identify. In this paper, we(More)
The traditional center/surround Retinex enhancement algorithms only consider the illuminance. So it may amplify the noise. However image details will be lost in the subsequent denoising process. In this paper, we propose an illuminance-reflectance model(IRMNE) which can denoise the image taken in the low light and enhance it at the same time. IRMNE can(More)
In this paper, we present a method of estimating the vanishing point from the railway environment images. Vanishing point plays a very important role in the machine vision based railway-environment surveillance methods, e.g. estimating the pose of the camera, video segmentation and panorama. In the application of railway-environment surveillance, we most(More)
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