A nearly lossless compression system for Bayer pattern images of a capsule endoscopy
RIS ID
112217
Abstract
Image Compression is very important tool to reduce the complexity and the power consumption for applications that have limited size capacity such as capsule endoscopy. To reduce the power required to code and transmite the resulting data of the capsule images, research has mainly focused on reducing the complexity of the design of image compression system. This was either by utlizing interpolation technique to convert the resulting Bayer images into full colour images or by modifing colour transformation with structure conversion to dedicate the Bayer images to the available image compression systems. Both methods are in high power consumption, requiring long processing time and on-chip memory. Thus, this study aims to develop a nearly lossless image compression system with a novel method of subtraction schemefollowed by a linear prediction and Golomb-Rice. The results of this study shows an excellent compression ratio of 93% and high quality reconstructed images with PSNR of 42dB. These results and the high mean structure similarity index matching between the original and the decompressed images confirm the validity of the proposed image compression system. Since this new method has overcome the need for either colour transformation or structure separation units which were necessary units in the compression systems for capsule endoscopy in the existing literature, the power and the processing time which was required to run those units has been eliminated by our new method.
Publication Details
Q. Al-Shebani, P. Premaratne & P. James. Vial, "A nearly lossless compression system for Bayer pattern images of a capsule endoscopy," in 10th International Conference on Signal Processing and Communication Systems (ICSPCS), 2016, pp. 1-6.