Performance of Predictive Coders for Wireless Capsule Endoscopy Image Compression
Caren Babu1, D. Abraham Chandy2
1Caren Babu, Department of Electronics and Communication Engineering, Karunya Institute of Technology and Sciences, India.
2D. Abraham Chandy*, Department of Electronics and Communication Engineering, Karunya Institute of Technology and Sciences, India.
Manuscript received on January 01, 2020. | Revised Manuscript received on January 20, 2020. | Manuscript published on January 30, 2020. | PP: 3094-3098 | Volume-8 Issue-5, January 2020. | Retrieval Number: E6388018520/2020©BEIESP | DOI: 10.35940/ijrte.E6388.018520
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Wireless capsule endoscopy is a medical diagnostic technique developed for the endoscopic examination of the small bowel. The encoder module is the core of the wireless capsule endoscopic system impacting on power and area requirement for the hardware implementation of the capsule. One of the remarkable features of the endoscopic image is that the neighboring pixels are highly correlated. Two predictive coding techniques are considered in this work exploiting the above fact. The first predictive coder i.e., DPCM coder is based on previous horizontal neighboring pixel, whereas the second predictive coder is based on adjacent horizontal and diagonal neighbors. The performance of the predictive coders is tested with 41 small bowel type endoscopic images available in the Gastrolab dataset. The results show that the average compression rate and peak signal to noise ratio attained by DPCM coder and newly tested predictive coder are 66.37 % & 73.03 % and 32.17 dB & 35.55 dB, respectively.
Keywords: Compression, DPCM, Endoscopic image, Gastrolab, Predictive coder.
Scope of the Article: Measurement & Performance Analysis.