Multi-level denoising and enhancement method based on wavelet transform for mine monitoring |
| |
Authors: | Zhao Yanqin |
| |
Affiliation: | Computer and Information Engineering College, Heilongjiang Institute of Science and Technology, Harbin 150027, China |
| |
Abstract: | Based on low illumination and a large number of mixed noises contained in coal mine, denoising with one method usually cannot achieve good results, so a multi-level image denoising method based on wavelet correlation relevant inter-scale is presented. Firstly, we used directional median filter to effectively reduce impulse noise in the spatial domain, which is the main cause of noise in mine. Secondly, we used a Wiener filtration method to mainly reduce the Gaussian noise, and then finally used a multi-wavelet transform to minimize the remaining noise of low-light images in the transform domain. This multi-level image noise reduction method combines spatial and transform domain denoising to enhance benefits, and effectively reduce impulse noise and Gaussian noise in a coal mine, while retaining good detailed image characteristics of the underground for improving quality of images with mixing noise and effective low-light environment. |
| |
Keywords: | Median filter Wiener filter Wavelet transform Image denoising Image enhancement |
本文献已被 ScienceDirect 等数据库收录! |
|