A Differential Privacy Image Publishing Method Based on Wavelet Transform

Image is an important information-bearing medium with many important attributes. If the image data is released directly, personal privacy will be compromised. This paper aims at how to use the method of differential privacy to protect the privacy of image data and make the image data have high usability. In this paper, a WIP method based on wavelet change is proposed. Firstly, wavelet transform is used to compress the image. Then, noise is added to the main features after transformation to obtain the published image satisfying the differential privacy. It solves the problem of low usability of large images and the problem that Fourier transform cannot deal with abrupt signal. Experimental results show that compared with similar methods in the frequency domain, the denoised image obtained by the proposed WIP method is more distinguishable and the information entropy is closer to the original image. The accuracy is 10% higher than other methods. Compared with other frequency-domain methods for image differential privacy protection, the proposed WIP method has higher usability and robustness.

Automated summary

This paper proposes a differential privacy protection method based on wavelet transform, which protects the privacy of image data by compressing and adding noise, solving the problems of low usability of large images and the inability of Fourier transform to handle abrupt signals.