Security and Privacy in New Computing Environments. Second EAI International Conference, SPNCE 2019, Tianjin, China, April 13–14, 2019, Proceedings

Research Article

Zone Based Lossy Image Compression Using Discrete Wavelet and Discrete Cosine Transformations

Download
130 downloads
  • @INPROCEEDINGS{10.1007/978-3-030-21373-2_62,
        author={Nafees Ahmad and Khalid Iqbal and Lansheng Han and Naeem Iqbal and Muhammad Abid},
        title={Zone Based Lossy Image Compression Using Discrete Wavelet and Discrete Cosine Transformations},
        proceedings={Security and Privacy in New Computing Environments. Second EAI International Conference, SPNCE 2019, Tianjin, China, April 13--14, 2019, Proceedings},
        proceedings_a={SPNCE},
        year={2019},
        month={6},
        keywords={Lossy image compression Discrete Cosine Transform Discrete Wavelet Transform},
        doi={10.1007/978-3-030-21373-2_62}
    }
    
  • Nafees Ahmad
    Khalid Iqbal
    Lansheng Han
    Naeem Iqbal
    Muhammad Abid
    Year: 2019
    Zone Based Lossy Image Compression Using Discrete Wavelet and Discrete Cosine Transformations
    SPNCE
    Springer
    DOI: 10.1007/978-3-030-21373-2_62
Nafees Ahmad1,*, Khalid Iqbal2,*, Lansheng Han1,*, Naeem Iqbal2,*, Muhammad Abid3,*
  • 1: Huazhong University of Science and Technology
  • 2: COMSATS University Islamabad
  • 3: Shandong University
*Contact email: nafees@hust.edu.cn, khalidiqbal@cuiatk.edu.pk, hanlansheng@hust.edu.cn, fa15-rcs-015@ciit-attock.edu.pk, emadilabid.b122@mail.sdu.edu.cn

Abstract

Due to the huge volume of image data generation in numerous domains, image compression has got the attention of researchers to minimize redundant image contents for efficient handling and transmission. However, a small region of interest (ROI) in the whole image is a major challenge in image compression. In this perspective, lossless image compression techniques have a low compression rate, and lossy image compression approaches, like JPEG, JPEG2000 and HD Photo, slightly loose data with high compression ratio. High compression ratio of lossy image compression helps in saving storage and fast transfer of data. In this paper, we proposed new DWT based zoning technique in combination with DCT for image compression. DWT divides an image into LL, LH, HL and HH frequencies and Zoning is further dividing these images into four parts as an input to DCT one after another. The output of DCT on each zone is then combined into a compressed bitstream image. Extensive experimentation is performed on various common images to compare the results with JPEG, JPEG2000 and HD Photo methods. Our ZDD methods remarkably performed better than the aforementioned techniques.