An Ingenious Design of a High Performance-Low Complexity Image Compressor for Wireless Capsule Endoscopy

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.

Frontiers of Robotic Gastroscopy: A Comprehensive Review of Robotic Gastroscopes and Technologies

“…However, even now telemedicine seems still limited to follow-up care of patients with inflammatory bowel and liver disease [ 98 , 99 ]. In the light of recent developments in the field of mobile-cloud-assisted, wireless body sensors and remote robotic endoscopic technologies, patients could undergo a spectrum of various diagnostic procedures amid their daily routines [ 100 , 101 , 102 ]. Internet-based remote visit has been proofed as an effective and safe option to deliver care at a distance, limiting the risks of infection [ 103 ]; a detailed description of wireless body sensors is out of the scope of this review and has been extensively reviewed in [ 104 , 105 ].…”

An Ingenious Application-Specific Quality Assessment Methods for Compressed Wireless Capsule Endoscopy Images

“…The selected images are in RGB format with different resolutions. The images from this database were used in the performance evaluation of several image compression algorithms [2], [17].…”

“…Second, the sharp transition boundary between the corner regions (non-informative regions) and circular visual region of the endoscopic capsule image is highly affected by lossy image compression algorithms that involve sub-sampling and quantization such as DCT-based [15] and DWT-based [16] algorithms. Similarly, the quantization and subsampling operation in DPCM-based [17], [18], and error due to inadequate side information in distributed video coding algorithms [19]. However, this region has no significant information relevant to the diagnosis of abnormalities in the gastrointestinal tract.…”