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Related Experiment Video

Updated: Apr 18, 2026

High-resolution, High-speed, Three-dimensional Video Imaging with Digital Fringe Projection Techniques

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Published on: December 3, 2013

An improved YEF-DCT based compression algorithm for video capsule endoscopy.

Atahar Mostafa, Tareq Khan, Khan Wahid

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference

|January 9, 2015

Summary

This summary is machine-generated.

This study introduces an efficient integer discrete-cosine-transform (DCT) based image compression algorithm for wireless capsule endoscopy. The novel YEF color space and quantization scheme achieve 85% compression with high image quality (52 dB PSNR).

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Area of Science:

Biomedical Engineering
Medical Imaging
Signal Processing

Background:

Video capsule endoscopy requires high-quality image transmission with minimal hardware and battery power.
Efficient image compression is crucial for wireless capsule endoscopy to conserve bandwidth and transmission power.

Purpose of the Study:

To develop and evaluate an efficient image compression algorithm for wireless capsule endoscopy.
To address the challenges of image quality, hardware constraints, and power consumption in capsule endoscopy.

Main Methods:

Analysis of thousands of human endoscopic images to identify key intestinal features.
Implementation of a low-complexity, lossless YEF color space converter.
Development of a low-cost quantization scheme with variable chroma sub-sampling.

Main Results:

The proposed integer DCT-based algorithm achieves an average compression ratio of 85%.
The system maintains a high image quality index, with a peak-signal-to-noise ratio (PSNR) of 52 dB.
The YEF color space converter requires minimal adders and shift operations for implementation.

Conclusions:

The developed compression algorithm is highly effective for wireless capsule endoscopy applications.
The combination of the YEF color space and quantization scheme significantly enhances compression efficiency while preserving image quality.
This approach offers a practical solution for transmitting high-quality endoscopic images under power and bandwidth limitations.