摘要
通过对空间目标图像的特性进行分析,提出一种针对星空背景图像在保留恒星同时去除混合噪声的方法。该方法首先利用小波局部模极大值的多尺度相关性检测出图像边缘,再利用基于梯度分析的改进阈值方法对非边缘小波系数进行萎缩,最后由小波系数重构去噪后图像。实验证明该方法能够有效地去除高斯和椒盐混合噪声,使图像峰值信噪比提高5-10dB,并较好地保留图像边缘和有效恒星信息。
A space target image denoising method based on wavelet was proposed to suppress mixed noise while preserving dim stars and edges. First, the image edges were computed according to the multi-scale interrelationship of the local modulus maxima on wavelet. Then, an improved thresholding method with gradient analysis was carried out to shrink the non-edge wavelet coefficients. Finally, denoising image was reconstructed from wavelet coefficients. Experiments show that such a method gives superior results compared with median filters and soft-thresholding method, effectively removes the mixed noise and improves Peak Signal to Noise Ratio（PSNR） by 5-10dB. In addition, the method also preserves the detailed information and stars of the original image.
出处
《电子器件》
CAS
2009年第3期716-720,共5页
Chinese Journal of Electron Devices
基金
中国空间技术研究院CAST创新基金项目资助(CAST2000607)
国家自然科学基金项目(60802043)
关键词
图像去噪
小波变换
空间目标
混合噪声
image denoising
wavelet transform
space target
mixed noise
