提升小波变换域矿井光照不均匀图像双直方图均衡化增强

Bi-histogram Equalization Enhancement of the Undermine Uneven Illumination Image Based on Lifting Wavelet Transform Domain

由于矿井光照不均匀,加之大量粉尘附着于监控摄像头表面,导致获取的视频图像对比度不高且含有大量随机分布的颗粒状噪声。为提高该类图像的对比度,充分发挥矿井视频监控系统的效能,基于提升小波变换(Lifting wavelet transform LWT),提出了一种矿井不均匀光照图像的自适应增强算法。首先采用直方图规定化算法(Histogram specification,HS)对获取的矿井图像进行初步增强;其次对初步增强后的图像进行提升小波变换,由于图像中的随机噪声主要集中分布于高频小波分解系数中,低频小波分解系数基本不存在噪声,故保留低频小波分解系数,对高频小波分解系数提出了一种基于反正弦函数的改进阈值函数去噪模型进行噪声抑制;然后对低频小波分解系数和去噪后的高频小波分解系数进行重构,得到不含噪声的矿井图像;最后采用双直方图均衡化算法(Bi-histogram equalization,BHE)对去噪后的图像进行进一步增强。将所提算法分别与直方图规定化、反锐化掩膜、小波阈值去噪等算法进行性能对比,并采用峰值信噪比(Peak noise to ratio,PSNR)、均方根误差(Root mean square error,RMSE)以及边缘保持指数(Edge protection index,EPI)等指标对试验结果进行评价,结果表明:所提算法对于矿井光照不均匀图像的处理效果相对于其余算法而言效果较优,对于高效处理矿井视频图像有一定的参考价值。

Undermine illumination is uneven and the surfaces of surveillance cameras are covered by a large number of dust,so,the contrast of obtained video surveillance image is low and there are a large number of granular noise random distributed in video surveillance image.In order to improve the contrast of this kind of image and make full of the effectiveness of the underground video surveillance system,based on lifting wavelet transform（LWT）,a adaptive enhancement method of underground uneven illumination image algorithm is proposed.Firstly,the histogram specification（HS）algorithm is adopted to conduct preliminary enhancement of the underground uneven illumination image;secondly,the preliminary enhancement image is conducted lifting wavelet transform,the low-frequency wavelet decomposition coefficient,based on the characteristics of them,the low-frequency wavelet decomposition coefficient is remained unchanged,a new wavelet thresholding function model based on the arcsine function is put forward to filter out the noise distributed in the high-frequency wavelet decomposition coefficients;then,the low-frequency wavelet decomposition coefficients and the filtered high-frequency wavelet decomposition coefficients are conducted refactoring,the underground image without noise is obtained;finally,the bi-histogram equalization（BHE）algorithm is used to improve the visual effects of the filtered underground image without noise.The performances of the algorithm proposed in this paper,histogram specification,counter-peaked mask and wavelet thresholding method are analyzed,besides that,peak signal noise to ratio（PSNR）,root mean square error（RMSE）and edge protection index（EPI）are adopted to evaluate the preference of the above algorithms,the results show that the processing effects of the algorithm proposed in this paper is superior to the other algorithms,if has some reference for processing the undermine video surveillance image.