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Medical Ultrasound Image Compression Using Edge Detection

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Intelligent Sustainable Systems

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 213))

Abstract

In computer era, image compression is one of the thirstiest requirements. The Compression ratio of existing algorithms is less so a new compression algorithm is needed as the urgent demand. A new image compression algorithm is proposed in this research paper using a Discrete Fourier Transform (DFT), Discrete Wavelet Transform (DWT), and Edge Detection. Daubechis wavelet family is used for DWT process. For the edge detection process, the canny edge detection method is used. A Real part of Fourier transform is used for further compression. The Wavelet method compresses the data, and the morphological process thickens the edges of detail sub-images. Canny edge detection detects edges and the information is preserved. The non-edge information is erased from the detail portion. The proposed algorithm provides a better compression ratio than the existing methods. It also produces high PSNR values.

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Author information

Authors and Affiliations

  1. Department of Computer Applications, Alagappa University, Karaikudi, India

    T. Manivannan & A. Nagarajan

Authors
  1. T. Manivannan
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  2. A. Nagarajan
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Editor information

Editors and Affiliations

  1. Gnanmani College of Engineering and Technology, Namakkal, Tamil Nadu, India

    Jennifer S. Raj

  2. Department of Business Administration, The Gerald Schwartz, School of Business, St. Francis Xavier University, Nova Scotia, NS, Canada

    Ram Palanisamy

  3. Department of Computer Engineering and Informatics, University of Patras, Patra, Greece

    Isidoros Perikos

  4. Department of Computer Science, Kennesaw State University, Kennesaw, GA, USA

    Yong Shi

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© 2022 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Manivannan, T., Nagarajan, A. (2022). Medical Ultrasound Image Compression Using Edge Detection. In: Raj, J.S., Palanisamy, R., Perikos, I., Shi, Y. (eds) Intelligent Sustainable Systems. Lecture Notes in Networks and Systems, vol 213. Springer, Singapore. https://doi.org/10.1007/978-981-16-2422-3_48

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