利用MLT和SRS的混合图像融合与去噪算法

摘要

Airning at the problem of noise removal in image fusion,a hybrid image fusion and denoising algorithm based on multi-level transformation (MLT) and signal sparse representation (SRS) is proposed in this paper.A hybrid model is designed to perform the shear transform,and the MLT decomposition is used to thresholding the system.The sliding window technique and the translation invariance are used to form sparse representation for image fusion.The SRS algorithm is used to remove the noise in the source image.The experimental results show that the algorithm reduces the contrast and spectral information distortion of the fused image,shows high quality visual fusion effect,and maintains high PSNR values at different noise levels.%针对图像融合中的去噪声问题,提出一种基于多尺度变换(MLT)和信号稀疏表示(SRS)的混合图像融合与去噪算法,构建混合模型进行剪切变换,阈值化处理MLT分解后的各个系数值,运用滑动窗口技术和平移不变性形成稀疏表示进行图像融合,运用SRS算法去除源图像中的噪声.实验结果表明该算法减少了融合图像的对比度和光谱信息失真情况,显示出高质量的视觉融合效果,在不同噪声水平下能保持较高的PSNR值.