Range-gated laser image compression and encryption scheme based on bidirectional diffusion

Li, Jinqing; Sheng, Yaohui; Di, Xiaoqiang; Mu, Yining

doi:10.1007/s11801-021-1003-8

Cited by 3 publications

(2 citation statements)

References 16 publications

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“…With the rapid development of mobile communication technology, image transmission plays an important role in communication. However, due to the limitation of communication bandwidth and storage resources, efficient image compression has become an urgent need to improve transmission efficiency and reduce resource overhead [10][11] . Based on the principle of CNN, this paper will discuss how to use deep learning technology for effective compression in mobile communication image transmission.…”

Section: Compression Principle Of Mobile Communication Image Transmis...mentioning

confidence: 99%

Design of mobile communication image transmission compression algorithm based on convolutional neural network

Zhu

2024

Second International Conference on Physics, Photonics, and Optical Engineering (ICPPOE 2023)

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With the popularization of mobile communication applications, image transmission plays an increasingly important role in communication. However, due to the limitation of communication bandwidth and storage resources, efficient image compression has become an urgent need. The purpose of this study is to design an innovative mobile communication image transmission compression algorithm by introducing the deep learning technology of convolutional neural network (CNN). In this algorithm, through the feature learning of convolution level and the hierarchical structure of CNN, the abstract features in the image are gradually extracted. This feature extraction process can not only capture the texture and structure information of the image effectively, but also has the advantage of resisting the common information loss problem in traditional compression methods. In order to enhance the learning ability of the network, we introduce residual connection, which improves the network's long-range dependence and attention to important areas. Experimental results show that compared with traditional compression methods, the algorithm based on CNN can maintain higher image quality at the same compression rate. The algorithm is more universal and can meet the needs of mobile communication image transmission in different types and scenarios. In addition, the impact on transmission quality is relatively small, and it can maintain good visual effects even at high compression rate.

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Section: Compression Principle Of Mobile Communication Image Transmis...mentioning

confidence: 99%

Design of mobile communication image transmission compression algorithm based on convolutional neural network

Zhu

2024

Second International Conference on Physics, Photonics, and Optical Engineering (ICPPOE 2023)

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“…To boost encryption effectiveness, in addition to using chaotic systems with high real-time performance, the problem should be solved from the image itself, such as compressing and encrypting the image [ 22 , 23 , 24 ]. Unfortunately, most compression algorithms lead to lossy image decryption, and any degradation of image quality may lead to misdiagnosis, so most methods of image compression are not suitable for medical images.…”

Section: Introductionmentioning

confidence: 99%

An Encryption Algorithm for Region of Interest in Medical DICOM Based on One-Dimensional eλ-cos-cot Map

Meng

et al. 2022

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Today, with the rapid development of the Internet, improving image security becomes more and more important. To improve image encryption efficiency, a novel region of interest (ROI) encryption algorithm based on a chaotic system was proposed. First, a new 1D eλ-cos-cot (1D-ECC) with better chaotic performance than the traditional chaotic system is proposed. Second, the chaotic system is used to generate a plaintext-relate keystream based on the label information of a medical image DICOM (Digital Imaging and Communications in Medicine) file, the medical image is segmented using an adaptive threshold, and the segmented region of interest is encrypted. The encryption process is divided into two stages: scrambling and diffusion. In the scrambling stage, helical scanning and index scrambling are combined to scramble. In the diffusion stage, two-dimensional bi-directional diffusion is adopted, that is, the image is bi-directionally diffused row by column to make image security better. The algorithm offers good encryption speed and security performance, according to simulation results and security analysis.

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Performance Enhancement of Bit-Level XOR Compressed Image OFDM Transmission Systems

Xue

Wang

2022

Mobile Information Systems

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The bit error rate (BER) formula of the M-QAM system is derived under nonequally likely condition of the constellation points, from which improving the BER performance of the M-QAM system by optimizing the probability distribution of constellation points is identified. Based on the analysis, the bit-level XOR method is employed to encrypt the image data and modify the probability distribution of the constellation points. The simulation results show that bit-level XOR is helpful to obtain a better probability distribution of the 16-QAM system compared to that without bit XOR and hence can improve the BER performance of the proposed OFDM transmission system. Simulation results based on test images over the AWGN channel further confirm that the reliability of the OFDM transmission system and the reconstructed quality of the compressed image are both significantly enhanced using bit-level XOR operation.

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Range-gated laser image compression and encryption scheme based on bidirectional diffusion

Cited by 3 publications

References 16 publications

Design of mobile communication image transmission compression algorithm based on convolutional neural network

Design of mobile communication image transmission compression algorithm based on convolutional neural network

An Encryption Algorithm for Region of Interest in Medical DICOM Based on One-Dimensional eλ-cos-cot Map

Performance Enhancement of Bit-Level XOR Compressed Image OFDM Transmission Systems

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