JOURNAL ARTICLE

Near lossless medical image compression using JPEG-LS and cubic spline interpolation

Tsung‐Ching LinChien‐Wen ChenShi-Huang ChenTrieu‐Kien Truong

Year: 2008 Journal:   Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE Vol: 7072 Pages: 70721G-70721G   Publisher: SPIE

Abstract

In this paper, a near lossless medical image compression scheme combining JPEG-LS with cubic spline interpolation (CSI) is presented. The CSI is developed to subsample image data with minimal distortion and to achieve image compression. It has been shown in literatures that the CSI can be combined with the transform-based image compression algorithm to develop a modified image compression codec, which obtains a higher compression ratio and a better subjective quality of reconstructed image than the standard transform-based codecs. This paper combines the CSI with lossless JPEG-LS to form the modified JPEG-LS scheme and further makes use of this modified codec to medical image compression. By comparing with the JPEG-LS image compression standard, experimental results show that the compression ratio increased over 3 times for the proposed scheme with similar visual quality. The proposed scheme reduces the loading for storing and transmission of image, therefore it is suitable for low bit-rate telemedicine application. The modified JPEG-LS can reduce the loading of storing and transmitting of medical image.

Keywords:
Lossless compression Lossy compression JPEG Image compression Computer science Lossless JPEG Computer vision Artificial intelligence Data compression ratio Data compression Compression ratio Codec Image quality Texture compression Algorithm Image processing Image (mathematics) Computer hardware

Metrics

2
Cited By
0.00
FWCI (Field Weighted Citation Impact)
13
Refs
0.07
Citation Normalized Percentile
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Citation History

Topics

Advanced Data Compression Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Advanced Image Processing Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Image and Signal Denoising Methods
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
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