Journal of Real-Time Image Processing

, Volume 8, Issue 1, pp 5–19 | Cite as

Subsample-based image compression for capsule endoscopy

Special Issue

Abstract

The key design challenge in capsule endoscopic system is to reduce the area and power consumption while maintaining acceptable video quality. In this paper, a subsample-based image compressor for such endoscopic application is presented. The algorithm is developed around some special features of endoscopic images. It consists of a differential pulse coded modulation followed by Golomb-rice coding. Based on the nature of endoscopic images, several subsampling schemes on the chrominance components are applied. This scheme is particularly suitable to work with any commercial low-power image sensors that outputs image pixels in a raster scan fashion, eliminating the need of memory buffer, as well as temporary storage (as needed in transform coding schemes). An image corner clipping algorithm is also presented. The reconstructed images have been verified by medical doctors for acceptability. The proposed algorithm has a very low complexity and is suitable for the VLSI implementation. Compared to other transform-based algorithms targeted to capsule endoscopy, the proposed raster-scan-based scheme performs very strongly with a compression ratio of 80% and a very high reconstruction PSNR (over 45 dB).

Keywords

Differential pulse coded modulation Capsule endoscopic application Golomb coding Image compression 

Notes

Acknowledgments

The authors would like to acknowledge the Natural Science and Engineering Research Council of Canada (NSERC) for its support to this research work. The authors are also indebted to the Canadian Microelectronics Corporation (CMC) for providing the hardware and software infrastructure used in the development of this design. The authors would also like to express special gratitude to Dr. Stefan Kriegler from Royal University Hospital, Saskatoon, Dr. Sheldon Wiebe from the Department of Medical Imaging, University of Saskatchewan, Dr. Gary May from the Division of Gastroenterology, University of Toronto, Dr. Nasir M. Jaffer from Mount Sinai Hospital, Toronto, and Dr. Narinder Paul from the Department of Medical Imaging, Toronto General Hospital for providing valuable opinion in the image quality assessment survey.

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Copyright information

© Springer-Verlag 2011

Authors and Affiliations

  1. 1.Department of Electrical and Computer EngineeringUniversity of SaskatchewanSaskatoonCanada

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