Image Compression using Single Layer Linear Neural Networks

被引:4
|
作者
Arunapriya, B. [1 ]
Devi, D. Kavitha [1 ]
机构
[1] PSGR Krishnammal Coll Women, Coimbatore 641004, Tamil Nadu, India
来源
PROCEEDINGS OF THE INTERNATIONAL CONFERENCE AND EXHIBITION ON BIOMETRICS TECHNOLOGY | 2010年 / 2卷
关键词
Wavelet; Modified Single Layer Linear Forward Only Counter propagation; Clustering; Distance Metrics;
D O I
10.1016/j.procs.2010.11.045
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Images and text form an integral part of website designing. Images have an engrossing appeal and that's why they attract more and more visitors. But, due to expensive bandwidth and time-consuming downloads; it has become essential to compress images. There are various methods and techniques available to compress images. In this paper, an effective technique is introduced called Wavelet-Modified Single Layer Linear Forward Only Counter Propagation Network (MSLLFOCPN) technique to solve image compression. This technique inherits the properties of localizing the global spatial and frequency correlation from wavelets. Function approximation and prediction are obtained from neural networks. Consequently counter propagation network was considered for its superior performance and the research helps to propose a new neural network architecture named single layer linear counter propagation network (SLLC). Several benchmark images are used to test the proposed technique combined of wavelet and SLLC network. The experiment results when compared with existing and traditional neural networks shows that picture quality, compression ratio and approximation or prediction are highly enhanced. (C) 2010 Published by Elsevier Ltd
引用
收藏
页码:345 / 352
页数:8
相关论文
共 50 条
  • [21] Image compression by cellular neural networks
    Univ of Pennsylvania, Pennsylvania, United States
    IEEE Trans Circuits Syst I Fundam Theor Appl, 3 (205-215):
  • [22] Image compression with neural networks - A survey
    Jiang, J
    SIGNAL PROCESSING-IMAGE COMMUNICATION, 1999, 14 (09) : 737 - 760
  • [23] Neural networks for image and video compression
    Gorodilov, Artem
    Gavrilov, Dmitriy
    Schelkunov, Dmitriy
    2018 INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE: APPLICATIONS AND INNOVATIONS (IC-AIAI), 2018, : 37 - 41
  • [24] AUTOASSOCIATIVE NEURAL NETWORKS FOR IMAGE COMPRESSION
    BASSO, A
    KUNT, M
    EUROPEAN TRANSACTIONS ON TELECOMMUNICATIONS, 1992, 3 (06): : 593 - 598
  • [25] Image compression by cellular neural networks
    Venetianer, PL
    Roska, T
    IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-FUNDAMENTAL THEORY AND APPLICATIONS, 1998, 45 (03): : 205 - 215
  • [26] Image Compression with Artificial Neural Networks
    Kouamo, Stephane
    Tangha, Claude
    INTERNATIONAL JOINT CONFERENCE CISIS'12 - ICEUTE'12 - SOCO'12 SPECIAL SESSIONS, 2013, 189 : 515 - 524
  • [27] Single image dehazing using deep neural networks
    Hodges, Cameron
    Bennamoun, Mohammed
    Rahmani, Hossein
    PATTERN RECOGNITION LETTERS, 2019, 128 : 70 - 77
  • [28] Image Stitching with single-hidden layer feedforward Neural Networks
    Yan, Min
    Yin, Qian
    Guo, Ping
    2016 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN), 2016, : 4162 - 4169
  • [29] Image Compression Using Discrete Wavelet Transform and Convolution Neural Networks
    Kumar, Gottapu Santosh
    Rani, M. Laxmi Prasanna
    JOURNAL OF ELECTRICAL ENGINEERING & TECHNOLOGY, 2024, 19 (06) : 3713 - 3721
  • [30] Lossless compression for hyperspectral image using deep recurrent neural networks
    Jiqiang Luo
    Jiaji Wu
    Shihui Zhao
    Lei Wang
    Tingfa Xu
    International Journal of Machine Learning and Cybernetics, 2019, 10 : 2619 - 2629