融合提升小波阈值与多方向边缘检测的矿区遥感图像去噪

Denoising algorithm based on the fusion of lifting wavelet thresholding and multidirectional edge detection of remote sensing image of mining area

遥感图像在矿区生态修复、地质灾害监测与防治等方面发挥了重要作用,但由于矿区环境复杂,导致获取的遥感图像存在噪声,在很大程度上影响了后续的图像解译与分析。为此,融合图像边缘检测与噪声抑制思路,提出了一种基于提升小波阈值(lifting wavelet thresholding,LWT)与改进Prewitt算子边缘检测(improved edge dectction of Prewitt operator,IEDPO)的矿区遥感图像去噪算法(LWT-IEDPO)。首先,对原始遥感图像进行提升小波变换,在保留低频小波子带不作处理的情况下,设计了一种双参数阈值函数模型对高频子带进行自适应噪声抑制,经过小波逆变换获得初步去噪后的遥感图像;其次,为有效增强滤波后图像的细节信息,将经典Prewitt算子的检测模板扩展到0°,30°,60°,90°,120°和150°这6个方向,并设计了相应的检测结果融合规则,提出了改进的Prewitt算子来提取图像边缘轮廓,获得轮廓图像和非轮廓图像;然后,为了进一步改善视觉效果,针对非轮廓图像采用改进的Pal-King模糊算法提升对比度;最后,将增强后的非轮廓图像和轮廓图像进行叠加,实现对遥感图像的高清晰度复原。在MATLAB平台上,将所提出的遥感图像处理方法与经典硬阈值、软阈值模型以及2种已有的改进小波阈值算法进行对比,并引入峰值信噪比(peak signal to noise ratio,PSNR)和边缘保持指数(edge protection index,EPI)对各算法的噪声抑制性能进行定量分析和比较。研究表明所提方法能够有效实现遥感图像去噪,其总体性能优于其余4种算法。

Remote sensing image plays an important role in ecological restoration,geological disaster monitoring and prevention of mining area;nevertheless,due to the complex environment of mining area,the obtained remote sensing images of the mining area contains different kinds of intensity noise,which affects the subsequent image interpretation and analysis to a great extent.In this paper,the study ideas of image edge detection and noise suppression are effectively fused together,and the improved denoising method(LWT-IEDPO)of remote sensing image in mining area based on the fusion of lifting wavelet thresholding(LWT)and improved edge dectction of Prewitt operator(IEDPO)is proposed.According to the basic principal of the new method proposed in this paper,firstly,lifting wavelet transform is done for the original remote sensing image;under the condition that the low-frequency wavelet sub-band is left untreated,a two-parameters thresholding function model is designed for adaptive noise suppression of high-frequency sub-bands,and the remote sensing image after initial denoising is obtained by the operation of inverse lifting wavelet transform.Secondly,for the purpose of effectively enhancing the details of the filtered remote sensing image,the detection template of the classical Prewitt operator is extended to 6 directions of 0°,30°,60°,90°,120°and 150°,and the corresponding detection results fusion rules are proposed.The improved Prewitt operator is put forward to extract the image edge information of the filtered image,and the edge and non-edge image are obtained.Then,the visual effect non-edge image is further improved by adopting the improved Pal-King fuzzy algorithm.Finally,the goal of high definition restoration of the original remote sensing image is realized by the superimposition of the enhanced non-edge image and edge image.Based on MATLAB language,the proposed remote sensing image processing method is compared with the classical hard thresholding model,soft thresholding model and two existing improved wavelet thresholding algorithms;in addition,the two indices of peak signal to noise ratio(PSNR)and edge protection index(EPI)are used to conduct quantitative analysis and comparison of the performance of the above algorithms.The study results show that the goal of effectively filtering of noise remote sensing image can be realized effectively,and the overall performance of the proposed algorithm is better than that of the other four algorithms.