Research Of Semi-tensor Compressed Sensing Algorithm Optimization And Its Application

With the rapid development of the Internet of Things technology,various sensor networks have achieved more wide applications.These sensors generate a large amount of sensitive data,while facilitating social life.These data not only increase the transmission load of the channel,but also occupy a large amount of storage space,and put forward higher security requirements.In telemedicine systems,a large amount of sensitive data is involved in the data transmission process.Many vital signs require a high-level encryption scheme to protect their confidentiality.Other data also should ensure the accuracy of the information so that relevant personnel can make accurate judgment.Aiming at the requirements of confidentiality and accuracy in the data transmission process,this paper has carried out the research and analysis on the secure and efficient data transmission scheme in the field of telemedicine based on the semi-tensor compressed sensing algorithm.The main innovations and research results are described as follows:(1)This paper proposes a measurement matrix optimization method suitable for semi-tensor compressed sensing.According to the properties of semi-tensor product and compressed sensing algorithms,combined with the method of matrix singular value decomposition,this paper uses the Gram matrix which is constructed by the normalized semi-tensor product matrix to adjust the measurement matrix.Using the correspondence between the Gram matrix determinant and the vector linear independence,the correlation of the measurement matrix is reduced by adjusting the singular value of the Gram matrix,which can improve the image measurement effect,and enhance the image quality of the semi-tensor compressed sensing.The effects of the proposed optimization method on the matrix column mutual correlation and the improvement of the reconstructed image quality are verified and analyzed from both theoretical and experimental aspects.(2)This paper designs a secure and traceable data transmission scheme.Aiming at the image transmission requirements in the field of telemedicine,based on digital watermarking technology,perceptual hashing algorithm and proposed measurement matrix optimization method,a novel data transmission scheme is proposed.The digital watermarking technology hides the compressed and encrypted secret image,so that the ciphertext is not visible during the transmission process.The image fingerprint is generated by the perceptual hash algorithm,which can verify the image authenticity,and the image fingerprint chain is generated by combining multiple image fingerprints to provide the traceability of image authentication.Both theoretical analysis and simulation experiments show that the scheme can hide the encrypted image,provide the traceability of the authentication result,and ensure the quality of image transmission,which meets the actual requirements of the transmission in related fields.