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LOCO-I (LOw COmplexity LOssless COmpression for Images) is the algorithm at the results at the time (at the cost of high complexity), it could be argued that the improvement .. In the sequel, we assume that this term is tuned to cancel R. LOCO-I (LOw COmplexity LOssless COmpression for Images) is the . Faria, A method to improve HEVC lossless coding of volumetric medical images, Image . A. Lopes, R. d’Amore, A tolerant JPEG-LS image compressor foreseeing COTS. Liu Zheng-lin, Qian Ying2, Yang Li-ying, Bo Yu, Li Hui (), “An Improved Lossless Image Compression Algorithm LOCO-R”, International Conference On.

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For medical diagnostics, these distortions can lead to inaccurate diagnostics decisions. Moreover, the algorithms presented in these works are based on DCT which has computational complexity of O n log n and need buffer memory as described earlier. It is noted here that, medical implantable communication service MICS compatible RF transceivers that work at — MHz frequency, are the most suitable choice for transmitting data through human body [ 28 ].

At this first stage of the algorithm, RGB pixels are converted to YEF color space [ 5 ], which is suitable for CE image compression and efficient for hardware implementation. While designing the lossless compression algorithm, we have set the following design objectives:.

The proposed compressor works on a low complexity YEF color space and it has a computational complexity of O n with no buffer memory requirements for image storage.

An improved lossless image compression algorithm LOCO-R

While lossy compression algorithms for capsule endoscopy are in abundance, their lossless counterpart is only a few. Performance Evaluation in a Capsule Prototype In order to validate the performance of the proposed lossless compression algorithm in a real-world scenario, it is employed inside a capsule endoscopy prototype.

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Data Logger A microcontroller based data logger is used for storing image data [ 30 ]. If there was any error, then it requests the transmitter to resend the data-packet again. More simulations have been conducted with WLI and 15 NBI test endoscopy images and with standard images; average absolute difference AAD is used as given in Equation 9 as the statistical measure of dX:.

When comparing with JPEG-LS, the proposed algorithm has higher compression ratio, lower computational complexity such as static prediction and static k parameter and lower memory requirement. Open in a separate window.

Conflicts of Interest The authors declare no conflict of interest. In this experiment, anesthesia was applied to a live pig under test and the capsule prototype is place into its small intestine through surgery.

Captured NBI images from live pig’s intestine: The synthesis results of the proposed lossless compressor are summarized in Table 8. Both lossy and lossless image compression algorithms are found in the literature targeting capsule endoscopy application.

However, this unit is not offered for public purchase; instead they offer a low data-rate transceiver part ZL with data rate of kpbs [ 26 ] which is not even sufficient for imagge frames per sec application. It may generate very small variations in pixel values at the output stream which is visually unnoticeable to human eyes when displayed as an image.

Our experiments show that, in most cases, the intensity distribution of green in endoscopic images is very similar to that of blue component.

Images from different positions of GI tract. The proposed compressor has lower computational complexity and memory requirements than the work in [ 24 ]. Compression with other compression algorithms. Due to the rare occurrence of sharp edges in endoscopic images, the difference between the component values of two consecutive pixels is generally small.


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This article has been cited by other articles in PMC. In order to save wireless transmission power and bandwidth, an image compressor needs to be implemented losless an endoscopy capsule. A wireless narrowband imaging chip for capsule endoscope.

As the input NBI images are grayscale, only the luminance Y component is compressed and transmitted. The compressor works on a highly efficient YEF color space [ 5 ], which is specially designed to compress endoscopic images by analyzing the unique image properties.

An improved lossless image compression algorithm LOCO-R – Semantic Scholar

Lossles performance of the compressor has been validated imaye a miniature FPGA based capsule prototype and by performing ex-vivo and in-vivo trials with pig’s intestine and live pig respectively. The experimental setup is shown in Figure Electronic Capsule To make the hardware modular, the capsule is divided into four boards: Comparison of compressor with other works.

The endoscopic capsule runs on button batteries. However, these compressors both raster scan based and block based presented in the literature are lossy compressors which incur various levels of distortions in the reconstructed images.

Two-stage wireless capsule image compression with low complexity and high quality. Pig’s intestine is chosen for experiment due to its relatively similar gastrointestinal functions in comparison to humans [ 33 ]. Turcza [ 15 ]. Intensity distribution of color components of impeoved NBI image: