Video compression using improved diamond search hybrid teaching and learning-based optimization model

ABSTRACT

Video compression is necessary to recreate a video without sacrificing quality. Nowadays, researchers are focusing on global optimization approaches to determine the optical flow of the neighboring pixels in video processing. In this work, a novel improved diamond search-hybrid teaching-learning based optimization (IDS-HTLBO) methodology has been proposed to compress the videos and increase the video quality. This method uses a diamond search pattern with a secure number of search points for per frame of the video. The hybridization of DS algorithm and TLBO algorithm are applied in this methodology to reduce computational complexity. Moreover, this method reduces the computational unpredictability of block matching. The quality of the image was validated with 3D reconstruction by the structured light approaches. The experimental result shows that the proposed IDS-HTLBO algorithm achieves a maximum average value of 53.17 dB, 0.44 and 11.57 in terms of peak-to-signal-noise ratio, mean squared error, and compression ratio respectively.

KEYWORDS:

• Video compression
• diamond search pattern
• teaching and learning optimization
• compression ratio
• peak-to-signal noise ratio
• video processing
• computational complexity
• mean squared error

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Notes on contributors

B. Veerasamy

B. Veerasamy has completed B.E. degree in Electronics and Communication Engineering from Government College of Technology, Coimbatore and received the M.E. Degree in VLSI Design from PSG College of Technology, Coimbatore. He is currently working as Associate Professor in Department of Electronics and Communication Engineering at Kalasalingam Academy of Research and Education, Krishnankoil- 626126. Presently, he is doing Ph.D. under Anna University, Chennai. His research interest includes embedded systems, real-time image/video processing, video coding, and the associated VLSI and processor architectures.

B. Bharathi

B. Bharathi received the B.E. degree in electronics and communication engineering from Government College of Technology, Coimbatore, India, in 2007, and the M.E degree in VLSI Design from the Anna University, Coimbatore, India, in 2011. She is currently working as an Assistant Professor with the Department of Information Technology, Coimbatore Institute of Engineering and Technology, Coimbatore, India. Her current research interests include Low Power VLSI Design, Image Processing, Machine Learning.

A. Ahilan

A. Ahilan received Ph.D. from Anna University, India, and working as an Associate Professor in the Department of Electronics and Communication Engineering at PSN College of Engineering and Technology, India. His area of interest includes FPGA prototyping, Computer vision, the Internet of Things, Cloud Computing in Medical, biometrics, and automation applications. Served Guest editor in several journals of Elsevier, Benthom, IGI publishers. Also, have contributed original research articles in IEEE Transactions, SCI, SCIE, and Scopus indexed peer-review journals. He presented various international conference events like ASQED (Malaysia), ESREF (France). He is doing as a reviewer in IEEE Industrial Informatics, IEEE Access, Measurement, Multimedia Tools & Applications, Computer Networks, Medical systems, Computer & Electrical Engineering, neural computing and applications, Cluster Computing, IET Image Processing, and so on. He has IEEE and ISTE membership. He has worked as a Research Consultant at TCS, Bangalore, where he has guided many computer vision projects and Bluetooth Low Energy projects. Hands on programming in MATLAB, Verilog and python at various technical institutions around India.