ABSTRACT
The three colour intensity values red, green and blue are acquired in a single pixel on using a multi-sensor camera. The single sensor camera uses the colour filter array to grab only one intensity value in a pixel location. The reconstruction of the so-called raw image into a full colour image is called demosaicking. This paper proposes a novel framework for effective demosaicking combined with the compression over the input image using a modified grey wolf optimization algorithm. The demosaicking process is efficient in applying the Modified Grey Wolf Optimized wavelet compression to optimally select the coefficients and Modified Huffman Coding technique to the image before demosaicking. The proposed technique is evaluated by the Peak Signal Noise Ratio, Structural Similarity Index Measure and Feature Similarity Index Measure values and has proved both subjectively and objectively to have better demosaicking results.
Disclosure statement
No potential conflict of interest was reported by the authors.
Notes on Contributors
M. S. Safna Asiq received her B.Ed. degree from Tamil Nadu Teachers Education University, Chennai, in 2012, M.Sc. degree from N.M. Christian College, Marthandam, in 2014, and M.Phil. Computer Science from S.T. Hindu College, Nagercoil, in 2015. At present, she is pursuing research (Reg.No.12406) in the Department of Computer Science, Nesamony Memorial Christian College, Marthandam, affiliated to Manonmanium Sundaranar University, Abishekapatti, Tirunelveli, India. Her research interests include Image Processing, Neural Network, and Fuzzy Logic.
W. R. Sam Emmanuel received his doctoral degree in computer science in 2012 from Vinayaka Missions University, Salem. He received his M.Phil. (Computer Science) degree in 2002 from Manonmaniam Sundaranar University, Tirunelveli, and MCA from Bharathidhasan University, Salem. He is working as Associate Professor at Nesamony Memorial Christian College, Marthandam. His major research interests are Image Processing, Cryptography, Network Security, Segmentation, and Classification.
ORCID
M. S. Safna Asiq http://orcid.org/0000-0002-1627-2874