1-bit image compression and encryption method

Abstract

A 1-bit image compression and encryption method comprises the following steps: firstly, performing two-dimensional discrete wavelet transform for an original image to obtain a sparse coefficient matrix; then performing permutation for sparse coefficients by using a random permutation matrix; and then performing projection measurement for the permuted sparse coefficient matrix by using a Gaussian random matrix to obtain a measurement value; and finally, performing 1-bit quantification for the measurement value to obtain a ciphertext. According to the 1-bit image compression and encryption method disclosed by the invention, the image compression ratio can be increased, the security of encryption systems can be improved, and the image compression ratio and image reconstruction accuracy can be improved.

Description

technical field [0001] The invention relates to an image compression method. Especially involving a 1-bit image compression encryption method Background technique [0002] With the rapid development of information technology and Internet technology, people are increasingly dependent on network systems and network resources. The rapid growth of electronic data processing and electronic commerce applications on the Internet, as well as the recurring incidents of international terrorism, have increased the need for better protection of computers and the information they store, process and transmit. [0003] As a new information carrier, image has the characteristics of intuitive image, vividness and concreteness, and has been widely used in the Internet field. When storing and transmitting important images, in order to ensure image security, it is necessary to design safe and efficient image encryption technology to protect them. [0004] Traditional image encryption methods...

AI Technical Summary

Problems solved by technology

[0008] (1) The quantization depth of compressed data is high. The existing image compression and encryption methods generally use a quantization depth of more than 8 bits to quantize the compressed value. The amount of compressed data is still large, and the efficiency of data transmission and storage is low, so it is not suitable for Low-power, distributed application scenarios such as mobile devices or wearable devices

[0009] (2) The existing image compression and encryption methods will leak the energy information of the original image, do not have perfect confidentiality, and are easily cracked by external attacks

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