基于稀疏分解的指静脉图像去噪

手指静脉识别技术因其独特的优势,受到广泛的关注。然而由硬件系统获取的手指静脉图像常常含有严重的噪声、阴影等问题,所以对低质量的静脉图像的去噪成为了整个识别过程的关键。本文提出了一种基于稀疏分解的指静脉图像去噪新方法。基于稀疏分解的图像去噪是将含有噪声的图像信息进行稀疏分解,分解成稀疏成分和其他成分。其中的稀疏部分是有用信息,其他部分被认为是噪声,再由图像的稀疏部分重建原始信号,达到恢复原始信号并去除噪声的效果。本文根据指静脉图像的静脉的特点,应用高斯函数构造了过完备库。用合成图像和真实指静脉图像分别对新算法进行实验验证。实验结果证明,与传统的去噪算法相比,峰值信噪比提高1-2dB。

Denoising for finger vein image based on sparse decomposition

Finger vein recognition had attracted great attention for its unique advantages.For the finger vein images we obtained from the hardware system often contain severe noise,shadow and other issues,denoising of the low quality images had become the key to the recognition process.For this reason,a new image denoising method based sparse representation for finger vein image was proposed in this paper.Image denoising method based on image sparse decomposition is different from the traditional image denoising methods.In this method,image corrupted by noise is decomposed into two parts.One part is the image sparse components which are related to image information.Another part,which remains after the image sparse components are subtracted from the image,is regarded as noise.Image can be denoised by reconstructing image only with its sparse components.The over-complete dictionary with the vein features of finger vein images was constructed by using the Gaussian function.The performance of the new method was verified by both synthetic and real finger vein images. Experimental results show that this algorithm can get better PSNR 1-2 dB compared with the traditional denoising.