Abstract:

In order to effectively suppress the noise of images and improve the accuracy of infrared diagnosis of electrical equipment,a denoising method based on both the wavelet coefficients’inter-scale correlation and the bivariate shrinkage function is proposed to denoise the infrared images of porcelain sleeve cable terminals.In this method,first,the wavelet transform coefficients are separated into two sorts by means of fuzzy c-means clustering according to the calculated inter-scale correlation coefficients of wavelet coefficients,namely,the efficient coefficients and the invalid coefficients.Then,the invalid wavelet coefficients are directly set to zero,while the efficient wavelet coefficients are processed with the bivariate shrinkage function.Thus,the estimated values of image's wavelet coefficients are obtained.Finally,the estimated wavelet coefficients are used to reconstruct a denoised image.The denoising results of infrared images with noise show that,as compared with the traditional soft thresholding method,the proposed method is more effective because it improves both the signal-to-noise ratio and the mean square error.

Key words: image denoising, inter-scale correlation, wavelet transform, correlation coefficient, fuzzy c-means, bivariate shrinkage