RGB-Based Compressed Medical Imaging Using Sparsity Averaging Reweighted Analysis for Wireless Capsule Endoscopy Images
- Authors
- Magdalena, Rita; Rahim, Tariq; Pratama, I. Putu Agus Eka; Novamizanti, Ledya; Ramatryana, I. Nyoman Apraz; Raja, Aamir Younas; Shin, Soo Young
- Issue Date
- 2021
- Publisher
- IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
- Keywords
- Magnetic resonance imaging; Image reconstruction; Image coding; Signal to noise ratio; Medical diagnostic imaging; Image color analysis; Computed tomography; Compressed imaging; RGB-based; reweighted analysis; sparsity averaging; wireless capsule endoscopy
- Citation
- IEEE ACCESS, v.9, pp.147091 - 147101
- Journal Title
- IEEE ACCESS
- Volume
- 9
- Start Page
- 147091
- End Page
- 147101
- URI
- https://scholarworks.bwise.kr/kumoh/handle/2020.sw.kumoh/20302
- DOI
- 10.1109/ACCESS.2021.3124239
- ISSN
- 2169-3536
- Abstract
- Compressed medical imaging (CMI) is a medical image sampling process with several samples lower than the Nyquist-Shannon sampling theorem for efficient image sampling; therefore, speeds up the processing time of medical applications. In comparison to previous approaches focusing on single-layer images analysis, this paper proposes CMI using RGB-based sparsity averaging with reweighted analysis (RGB-SARA). The proposed RGB-SARA method is based on the spread spectrum (SS) sampling method, sparsity averaging (SA), basis pursuit denoise (BPDN) reconstruction method, and reweighted analysis (RA). The CS-based SS sampling method compresses each sample in the specific RGB layer followed by SA and BPDN with RA as a sparsity basis and to enhance the performance of CMI reconstruction, respectively. A detailed results analysis is presented in terms of signal-to-noise ratio (SNR), average SNR (ASNR), structural similarity index (SSIM), and processing time demonstrating the efficacy of the proposed RGB-SARA over conventional CMI, i.e., Haar, Daubechies 8 (Db8), and curvelet. A successful demonstration is presented proving that the proposed RGB-SARA is a potential of a new compression method for medical images with high visual quality.
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Collections - School of Electronic Engineering > 1. Journal Articles
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