Paper Info
Title
Lossless Compression in Bayer Color Filter Array for Capsule Endoscopy.
Abstract
This paper presents a compression algorithm for color filter array (CFA) images in a wireless capsule endoscopy system. The proposed algorithm consists of a new color space transformation (known as YLMN), a raster-order prediction model, and a single context adaptive Golomb-Rice encoder to encode the residual signal with variable length coding. An optimum reversible color transformation derivation model is presented first, which incorporates a prediction model to find the optimum color transformation. After the color transformation, each color component has been independently encoded with a low complexity raster-order prediction model and Golomb-Rice encoder. The algorithm is implemented using a TSMC 65-nm CMOS process, which shows a reduction in gate count by 38.9% and memory requirement by 71.2% compared with existing methods. Performance assessment using CFA database shows the proposed design can outperform existing lossless and near-lossless compression algorithms by a large margin, which makes it suitable for capsule endoscopy application.
Year
DOI
Venue
2017
10.1109/ACCESS.2017.2726997
IEEE ACCESS
Keywords
Field
DocType
Wireless capsule endoscopy,color filter array,lossless image compression,reversible color transformation
Computer vision,Gate count,Color space,Computer science,Color depth,Demosaicing,Artificial intelligence,Encoder,Color filter array,Data compression,Lossless compression
Journal
Volume
ISSN
Citations 
5
2169-3536
2
PageRank 
References 
Authors
0.40
14
3
Name
Order
Citations
PageRank
Mohammed, S.K.183.12
K. M. Mafijur Rahman220.74
Khan A. Wahid332738.08