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

Abstract

Video capsule endoscopy is a non-invasive technique to receive images of intestine for medical diagnostics. The main design challenges of endoscopy capsule are accruing and transmitting acceptable quality images by utilizing as less hardware and battery power as possible. In order to save wireless transmission power and bandwidth, an efficient image compression algorithm needs to be implemented inside the endoscopy electronic capsule. In this paper, an integer discrete-cosine-transform (DCT) based algorithm is presented that works on a low-complexity color-space specially designed for wireless capsule endoscopy application. First of all, thousands of human endoscopic images and video frames have been analyzed to identify special intestinal features present in those frames. Then a color space, referred as YEF, is used. The YEF converter is lossless and takes only a few adders and shift operation to implement. A low-cost quantization scheme with variable chroma sub-sampling options is also implemented to achieve higher compression. Comparing with the existing works, the proposed transform coding based compressor performs strongly with an average compression ratio of 85% and a high image quality index, peak-signal-to-noise ratio (PSNR) of 52 dB.