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  • Open Access

    ARTICLE

    Color Image Compression and Encryption Algorithm Based on 2D Compressed Sensing and Hyperchaotic System

    Zhiqing Dong1, Zhao Zhang1,*, Hongyan Zhou2, Xuebo Chen2

    CMC-Computers, Materials & Continua, Vol.78, No.2, pp. 1977-1993, 2024, DOI:10.32604/cmc.2024.047233

    Abstract With the advent of the information security era, it is necessary to guarantee the privacy, accuracy, and dependable transfer of pictures. This study presents a new approach to the encryption and compression of color images. It is predicated on 2D compressed sensing (CS) and the hyperchaotic system. First, an optimized Arnold scrambling algorithm is applied to the initial color images to ensure strong security. Then, the processed images are concurrently encrypted and compressed using 2D CS. Among them, chaotic sequences replace traditional random measurement matrices to increase the system’s security. Third, the processed images are More >

  • Open Access

    ARTICLE

    DNA Computing with Water Strider Based Vector Quantization for Data Storage Systems

    A. Arokiaraj Jovith1, S. Rama Sree2, Gudikandhula Narasimha Rao3, K. Vijaya Kumar4, Woong Cho5, Gyanendra Prasad Joshi6, Sung Won Kim7,*

    CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 6429-6444, 2023, DOI:10.32604/cmc.2023.031817

    Abstract The exponential growth of data necessitates an effective data storage scheme, which helps to effectively manage the large quantity of data. To accomplish this, Deoxyribonucleic Acid (DNA) digital data storage process can be employed, which encodes and decodes binary data to and from synthesized strands of DNA. Vector quantization (VQ) is a commonly employed scheme for image compression and the optimal codebook generation is an effective process to reach maximum compression efficiency. This article introduces a new DNA Computing with Water Strider Algorithm based Vector Quantization (DNAC-WSAVQ) technique for Data Storage Systems. The proposed DNAC-WSAVQ… More >

  • Open Access

    ARTICLE

    ELM-Based Shape Adaptive DCT Compression Technique for Underwater Image Compression

    M. Jamuna Rani1,*, C. Vasanthanayaki2

    Computer Systems Science and Engineering, Vol.45, No.2, pp. 1953-1970, 2023, DOI:10.32604/csse.2023.028713

    Abstract Underwater imagery and transmission possess numerous challenges like lower signal bandwidth, slower data transmission bit rates, Noise, underwater blue/green light haze etc. These factors distort the estimation of Region of Interest and are prime hurdles in deploying efficient compression techniques. Due to the presence of blue/green light in underwater imagery, shape adaptive or block-wise compression techniques faces failures as it becomes very difficult to estimate the compression levels/coefficients for a particular region. This method is proposed to efficiently deploy an Extreme Learning Machine (ELM) model-based shape adaptive Discrete Cosine Transformation (DCT) for underwater images. Underwater More >

  • Open Access

    ARTICLE

    Three-Stages Hyperspectral Image Compression Sensing with Band Selection

    Jingbo Zhang, Yanjun Zhang, Xingjuan Cai*, Liping Xie*

    CMES-Computer Modeling in Engineering & Sciences, Vol.134, No.1, pp. 293-316, 2023, DOI:10.32604/cmes.2022.020426

    Abstract Compressed sensing (CS), as an efficient data transmission method, has achieved great success in the field of data transmission such as image, video and text. It can robustly recover signals from fewer Measurements, effectively alleviating the bandwidth pressure during data transmission. However, CS has many shortcomings in the transmission of hyperspectral image (HSI) data. This work aims to consider the application of CS in the transmission of hyperspectral image (HSI) data, and provides a feasible research scheme for CS of HSI data. HSI has rich spectral information and spatial information in bands, which can reflect… More >

  • Open Access

    ARTICLE

    Intelligent Satin Bowerbird Optimizer Based Compression Technique for Remote Sensing Images

    M. Saravanan1, J. Jayanthi2, U. Sakthi3, R. Rajkumar4, Gyanendra Prasad Joshi5, L. Minh Dang5, Hyeonjoon Moon5,*

    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 2683-2696, 2022, DOI:10.32604/cmc.2022.025642

    Abstract Due to latest advancements in the field of remote sensing, it becomes easier to acquire high quality images by the use of various satellites along with the sensing components. But the massive quantity of data poses a challenging issue to store and effectively transmit the remote sensing images. Therefore, image compression techniques can be utilized to process remote sensing images. In this aspect, vector quantization (VQ) can be employed for image compression and the widely applied VQ approach is Linde–Buzo–Gray (LBG) which creates a local optimum codebook for image construction. The process of constructing the… More >

  • Open Access

    ARTICLE

    Optimization Based Vector Quantization for Data Reduction in Multimedia Applications

    V. R. Kavitha1,*, M. Kanchana2, B. Gobinathan3, K. R. Sekar4, Mohamed Yacin Sikkandar5

    Intelligent Automation & Soft Computing, Vol.31, No.2, pp. 853-867, 2022, DOI:10.32604/iasc.2022.018358

    Abstract Data reduction and image compression techniques in the present Internet and multi-media age are essential to increase image and video capacity in relation to memory, network bandwidth use and safe data transmission. There have been a different variety of image compression models with varying compression efficiency and visual image quality in the literature. Vector Quantization (VQ) is a widely used image coding scheme that is designed to generate an efficient coding book that includes a list of codewords that assign the input image vector to a minimum distance of Euclidea. The Linde–Buzo–Gray (LBG) historically widely… More >

  • Open Access

    ARTICLE

    Medical Image Compression Method Using Lightweight Multi-Layer Perceptron for Mobile Healthcare Applications

    Taesik Lee1, Dongsan Jun1,*, Sang-hyo Park2, Byung-Gyu Kim3, Jungil Yun4, Kugjin Yun4, Won-Sik Cheong4

    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 2013-2029, 2022, DOI:10.32604/cmc.2022.019604

    Abstract As video compression is one of the core technologies required to enable seamless medical data streaming in mobile healthcare applications, there is a need to develop powerful media codecs that can achieve minimum bitrates while maintaining high perceptual quality. Versatile Video Coding (VVC) is the latest video coding standard that can provide powerful coding performance with a similar visual quality compared to the previously developed method that is High Efficiency Video Coding (HEVC). In order to achieve this improved coding performance, VVC adopted various advanced coding tools, such as flexible Multi-type Tree (MTT) block structure… More >

  • Open Access

    ARTICLE

    Compression of Grayscale Images in DRPE-based Encrypted Domain

    Osama S. Faragallah1,*, Ensherah A. Naeem2, Hala S. Elsayed3, Fathi E. Abd El-Samie4

    Intelligent Automation & Soft Computing, Vol.30, No.3, pp. 1019-1031, 2021, DOI:10.32604/iasc.2021.019185

    Abstract Compressing the encrypted images is considered an important issue in many applications such as cloud computing. From this perspective, this paper introduces an efficient approach for compression processing of images in the encrypted domain. The images are optically encrypted using the Double Random Phase Encoding (DRPE). The Joint Photographic Experts Group (JPEG) and the Set Partitioning in Hierarchical Trees (SPIHT) compression schemes have been used to compress the encrypted images. The process starts by converting the original image into an optical signal by an optical emitter like an optical source and encrypting it with DRPE. More >

  • Open Access

    ARTICLE

    Face Image Compression and Reconstruction Based on Improved PCA

    Yu Xue1,2,*, Chen Chen1, ChiShe Wang2, Linguo Li3, Romany F. Mansour4

    Intelligent Automation & Soft Computing, Vol.30, No.3, pp. 973-982, 2021, DOI:10.32604/iasc.2021.017607

    Abstract Face recognition technology has many usages in the real-world applications, and it has generated extensive interest in recent years. However, the amount of data in a digital image is growing explosively, taking up a lot of storage and transmission resources. There is a lot of redundancy in an image data representation. Thus, image compression has become a hot topic. The principal component analysis (PCA) can effectively remove the correlation of an image and condense the image information into a characteristic image with several main components. At the same time, it can restore different data images… More >

  • Open Access

    ARTICLE

    An Optimal Lempel Ziv Markov Based Microarray Image Compression Algorithm

    R. Sowmyalakshmi1,*, Mohamed Ibrahim Waly2, Mohamed Yacin Sikkandar2, T. Jayasankar1, Sayed Sayeed Ahmad3, Rashmi Rani3, Suresh Chavhan4,5

    CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 2245-2260, 2021, DOI:10.32604/cmc.2021.018636

    Abstract In the recent years, microarray technology gained attention for concurrent monitoring of numerous microarray images. It remains a major challenge to process, store and transmit such huge volumes of microarray images. So, image compression techniques are used in the reduction of number of bits so that it can be stored and the images can be shared easily. Various techniques have been proposed in the past with applications in different domains. The current research paper presents a novel image compression technique i.e., optimized Linde–Buzo–Gray (OLBG) with Lempel Ziv Markov Algorithm (LZMA) coding technique called OLBG-LZMA for… More >

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