Underwater sonar image denoising method based on dual-tree complex wavelet transform and PCA

Abstract

The invention provides an underwater sonar image denoising method based on dual-tree complex wavelet transform and PCA. The method comprises the following steps: performing the dual-tree complex wavelet transform to an underwater sonar image; converting the image from a space domain to a complex wavelet domain; maintaining a low-frequency approximate component obtained after the image is performed with three-layer dual-tree complex wavelet transform to be the same; processing a high frequency component of the image; using a PCA method to estimate noise energy in a high frequency sub-band so as to determine a threshold and using a hard threshold function to process a complex wavelet coefficient; performing the dual-tree complex wavelet transform to the processed complex wavelet coefficient so as to obtain the final denoising image. A traditional two dimension wavelet lacks translation invariance and direction selectivity. The method can overcome the above disadvantages. Image directivity information can be captured well. During the denoising, detail information, such as an image edge, texture and the like, can be protected.

Description

technical field [0001] The invention relates to a denoising method in the technical field of image processing. Background technique [0002] At present, there are many types of image denoising methods, such as mean filtering, median filtering, wavelet denoising and other commonly used methods. The mean filter is a linear spatial filter, which replaces the value of each pixel in the image with the average gray value of the neighborhood pixels determined by the mask. This process reduces the "sharp" change in the image gray, due to the typical Random noise consists of sharp transitions in gray levels, so mean-filtered image noise will be reduced. Median filtering is a nonlinear filtering method, which replaces the value of the pixel with the median gray value of the pixel in the neighborhood. It is widely used and has good denoising ability for many kinds of random noise. Wavelet denoising is also a very widely used denoising method. It converts the image into the wavelet do...

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Problems solved by technology

[0003] However, in terms of image edge, texture and other directional information preservation, the processing effect of these methods is not very ideal.

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