Wavelet Techniques for Medical Images Performance Analysis and Observations with EZW and Underwater Image Processing


The digitized image has an important role in the compression. Compression encodes the image using a certain algorithm with less number of bits and decompression decoded this image in original form using a different algorithm. The clinical environment and hospitals are moving towards digitization, computerization and centralization in the field of medical image processing. Content based compressions (CBC) techniques turns more considerable in the field of medical image processing and multimedia. However, CBC techniques alone are not adequate for all medical image processing applications. Therefore, in this paper, the EZW algorithm has been discussed with Haar wavelet and Bior4.4 technique on skeleton images with different type of image quality parameters. The analysis shows that the compression ratio (CR) of EZW with Bior4.4 on skeleton image is 44.19%, MSE is 527.73 and PSNR is 45.45. While, the CR of EZW with Haar on the same image is 40.31%, MSE is 699 and PSNR is 35.34 db. Further EZW can help precise capacity of amount, exterior area and other morph metric capacity of organic stuff, lacking removing them commencing the sea or in the marine environment.

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Correspondence to Javed Miya.

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Miya, J., Ansari, M.A. Wavelet Techniques for Medical Images Performance Analysis and Observations with EZW and Underwater Image Processing. Wireless Pers Commun 116, 1259–1272 (2021). https://doi.org/10.1007/s11277-020-07238-w

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  • Segmentation
  • Medical image compression
  • PSNR
  • MSE
  • CR
  • EZW
  • Underwater image processing
  • 3D modelling