3D DCT Based Image Compression Method for the Medical Endoscopic Application release_xa4wz4luqjb6zkbtg6pfbf3rzm

by Jiawen Xue, Li Yin, Zehua Lan, Mingzhu Long, Guolin Li, Zhihua Wang, Xiang Xie

Published in Sensors.

2021   Volume 21, Issue 5

Abstract

This paper proposes a novel 3D discrete cosine transform (DCT) based image compression method for medical endoscopic applications. Due to the high correlation among color components of wireless capsule endoscopy (WCE) images, the original 2D Bayer data pattern is reconstructed into a new 3D data pattern, and 3D DCT is adopted to compress the 3D data for high compression ratio and high quality. For the low computational complexity of 3D-DCT, an optimized 4-point DCT butterfly structure without multiplication operation is proposed. Due to the unique characteristics of the 3D data pattern, the quantization and zigzag scan are ameliorated. To further improve the visual quality of decompressed images, a frequency-domain filter is proposed to eliminate the blocking artifacts adaptively. Experiments show that our method attains an average compression ratio (CR) of 22.94:1 with the peak signal to noise ratio (PSNR) of 40.73 dB, which outperforms state-of-the-art methods.
In text/plain format

Archived Files and Locations

application/pdf  4.5 MB
file_ubcdgkiwabcjjiidna642ouebi
res.mdpi.com (web)
web.archive.org (webarchive)
Read Archived PDF
Preserved and Accessible
Type  article-journal
Stage   published
Date   2021-03-05
Language   en ?
DOI  10.3390/s21051817
PubMed  33807805
PMC  PMC7961525
Container Metadata
Open Access Publication
In DOAJ
In ISSN ROAD
In Keepers Registry
ISSN-L:  1424-8220
Work Entity
access all versions, variants, and formats of this works (eg, pre-prints)
Catalog Record
Revision: 039a7dbd-8e3e-4e18-8481-c4a087a2e300
API URL: JSON