对于CCD图像的非稳定高斯噪声,传统的Fourier变换法无法消除噪声,而小波变换在时域和频域同时具有优良的局部化特征,而且对高频采用逐渐精细的时域或空城步长可以聚焦到分析对象的任意细节,从而克服了传统Fourier变换固定步长等缺点,因此,小波变换法可消除这种噪声.本文在分析CCD图像噪声的基础上,利用小波变换和直方图分割方法对目标图像进行了降噪和边缘检测.试验证明此法行之有效.

For the unstable Gaussian noise of the CCD image, the conventional method of Fourier transform can not eliminate it,but the wavelet transform is the powerful tools of noise elimination,since the wavelet transform in both the time domain and frequency domain has the excellent localization features, and the arbitrary details of analyzed objects can be focused with gradually detailed time domain or frequency domain step at high frequency. Based on the analysis for the CCD image noise,the noise reduction and edge detection is realized with the method of wavelet transform and histogram division. The results show that the clear image edge can be made out after selecting a proper threshold with the histogram division method.