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Discrete wavelet transform applications in the IoMT

Discrete wavelet transform applications in the IoMT

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Recent research efforts have explored methods to achieve the wavelet transform as the most significant tool in medical image enhancement and processing. The problems of image fusion, compression, edge detection, denoising, and contrast enhancement can be handled by discrete wavelet transform (DWT) in the Internet of medical things (IoMT) framework. In this chapter, we present the novel DWT with orthogonal and biorthogonal wavelets application. Multiple applications of the wavelet transform in medical images have been submitted. These applications demonstrate the successful impact of applying DWT. The DWT has the ability to enhance the medical image and remove noise. The DWT in image compression can separately reduce the computational complexity into high and low frequency. This process reduces the image data in order to be able to store or transmit data in an efficient form. There are some advantages in using fusion based on DWT during other traditional methods, for example, reduced features and energy compaction. In digital watermarking, DWT technique is used for embedding and extraction of watermark in the original image.

Chapter Contents:

  • 4.1 Introduction
  • 4.2 The discrete wavelet transform
  • 4.3 DWT applications
  • 4.3.1 Image denoising
  • 4.3.2 Image fusion
  • 4.3.3 Image compression
  • 4.3.4 Image watermarking
  • 4.4 Conclusions
  • 4.5 Future work
  • References

Inspec keywords: medical image processing; Internet of Things; image denoising; edge detection; discrete wavelet transforms; image coding; biomedical communication; data compression; image watermarking; image enhancement; image fusion

Other keywords: image fusion; Internet of medical things framework; contrast enhancement; edge detection; orthogonal wavelets application; biorthogonal wavelets application; image compression; medical image enhancement; IoMT; DWT technique; image data

Subjects: Biology and medical computing; Image recognition; Integral transforms; Image and video coding; Computer networks and techniques; Integral transforms; Computer vision and image processing techniques; Computer communications; Biomedical communication; Biomedical measurement and imaging

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