Cardiff Metropolitan University
Browse
Compressive_Sampling_of_Color_Retinal_Image_Using_Spread_Spectrum_Fourier_Sampling_and_Total_Variant.pdf (2.04 MB)

Compressive Sampling of Color Retinal Image Using Spread Spectrum Fourier Sampling and Total Variant

Download (2.04 MB)
journal contribution
posted on 2022-05-23, 17:03 authored by Ledya Novamizanti, I Nyoman Apraz Ramatryana, Rita Magdalena, I Putu Agus Eka Pratama, Tariq Rahim, Young-Soo Shin

 In medical imaging, the application of retinal images demands a lot of retinal photos to analyze and requires efficient compression techniques for retinal image storage. Retinal images must meet stringent quality requirements for clinical data to be accurate and dependable. This paper proposes a compressive sampling (CS) framework for color retinal image (CRI) compression, which relies on spread spectrum Fourier sampling (SSFS) and total variant (TV)-based reconstruction method with three loops of RGB color space, referred to as RGB-TV. In CS, two procedures are performed, i.e., compression and CS reconstruction. In compression steps, SFFS is performed to get a compressed signal from the original CRI with a high compression ratio (CR). While in CS reconstruction, TV-norm and TV proximal operator are exploited for problem optimization to recover original CRI from a compressed signal. In addition, signal-to-noise ratio (SNR), structural similarity (SSIM), and reconstruction time are investigated for the performance metrics of the proposed RGB-TV. The computer simulation result shows that the proposed RGB-TV with a set of CRI of size 512 by 512 pixels can compress until CR = 10 which obtains mean SNR of 22 dB, SSIM 0.84, and reconstruction time of 2.2 seconds. 

History

Published in

IEEE Access

Publisher

IEEE

Version

  • VoR (Version of Record)

Citation

Novamizanti, L., Ramatryana, I.N.A., Magdalena, R., Pratama, I.P.A.E., Rahim, T. and Shin, S.Y. (2022) Compressive Sampling of Color Retinal Image Using Spread Spectrum Fourier Sampling and Total Variant. IEEE Access, 10, pp.42198-42207.

Electronic ISSN

2169-3536

Cardiff Met Affiliation

  • Cardiff School of Technologies

Cardiff Met Authors

Tariq Rahim

Copyright Holder

  • © The Authors

Language

  • en

Usage metrics

    School of Technologies Research - Journal Articles

    Licence

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC