Abstract
The wireless capsule endoscope (WCE) is a pill-sized device taking images, which are transmitting to an on-body receiver, while traveling through the digestive system. Since image data is transmitted through the human body, which is a harsh medium for electromagnetic wave propagation, noise may at times heavily corrupt the reconstructed image frames. A common way to combat noise is to use error-correcting codes. In addition one may also utilize inter- and intra frame correlation to reduce the impact of noise at the receiver side, placing no extra demand on the WCE. However, it is then of great importance that the chosen post processing methods do not alter the content of the image as this can lead to miss-detection by gastroenterologists. In this paper we will investigate the possibility for additional noise suppression and error concealment at the receiver side in a high intensity error regime. Due to the high correlation generally inherent in WCE video, satisfactory results are obtained, as concluded from both subjective tests with gastroenterologists as well as the structural similarity (SSIM) metric. More surprisingly, the subjective tests indicate that the inpainted frames in many cases can be used for clinical assessment. These results indicate that one can apply error reduction through post processing together with error-correcting codes to obtain a more noise-robust system without any further demand on the WCE.
Highlights
Severe diseases in the digestive system like inflammatory bowel disease and cancer reduce the quality of life, or even the length of life, in a huge number of patients
One way to cope with the larger amount of data that would result from increased frame rate and image resolution is to apply compression algorithms that reduces the large correlation among pixels typical for Wireless capsule endoscopy (WCE) frames, without introducing visible distortions
Experiments clearly showed that approach (i) was the only functioning option: scale-invariant feature transform (SIFT) followed by random sample consensus (RANSAC) is very robust to noise in the images we get into trouble when we try to decide the area in the image that should replace error blocks
Summary
Severe diseases in the digestive system like inflammatory bowel disease and cancer reduce the quality of life, or even the length of life, in a huge number of patients. One way to cope with the larger amount of data that would result from increased frame rate and image resolution is to apply compression algorithms that reduces the large correlation among pixels typical for WCE frames, without introducing visible distortions. One such algorithm was proposed by Kim et al in [4]. A great deal of these artifacts likely appear due to the fact that the available videostreams for WCE is already compressed (blocking artifacts are observed when the image is magnified, and these correspond to location of the DPCM related artifacts) This is reflected in the SSIM between original and compressed frame which is around 0.8 − 0.85. It is likely that future WCE’s will have higher framerate, making the above algorithm perform better in general
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