Abstract
Wireless Capsule Endoscopy is a state-of-the-art technology for medical diagnoses of gastrointestinal diseases. The amount of data produced by an endoscopic capsule camera is huge. These vast amounts of data are not practical to be saved internally due to power consumption and the available size. So, this data must be transmitted wirelessly outside the human body for further processing. The data should be compressed and transmitted efficiently in the domain of power consumption. In this paper, a new approach in the design and implementation of a low complexity, multiplier-less compression algorithm is proposed. Statistical analysis of capsule endoscopy images improved the performance of traditional lossless techniques, like Huffman coding and DPCM coding. Furthermore the Huffman implementation based on simple logic gates and without the use of memory tables increases more the speed and reduce the power consumption of the proposed system. Further analysis and comparison with existing state-of-the-art methods proved that the proposed method has better performance.
Highlights
For many years, doctors, in order to investigate diseases of the colon, have used classical colonoscopy tools
Similarities in colour range values and pixel sequences with the same or near the same values were observed. This characteristic gave us the motivation to examine the use of combinations of simple compression techniques and propose a compression algorithm dedicated for capsule endoscopy systems
After processing of all the capsule endoscopy images, we found that the range of the output of the Differential Pulse-Code Modulation (DPCM) encoder was from -127 and up to 128
Summary
Doctors, in order to investigate diseases of the colon, have used classical colonoscopy tools. A lossless image compression algorithm for WCE application is proposed. Despite the use of such many resources the maximum resolution that can compress is only VGA The bottleneck in this implementation is the huge amount of hardware resources needed to work. Lin et al [7] has designed and implemented an image compression scheme based on 2D-DCT His application is oriented in WCE usage. Performing multiplications, divisions, data synchronization, buffering, etc., results in more area occupation and higher power consumption than systems that are not so complicated This implementation is not lossless, but is near-lossless and has an image quality of 32.51 dB.
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