Open AccessIntelligent Image compression in Multi-agent system
Author(s) -
Jibanananda Mishra,
Bishnu Prasad Mishra,
Rabinarayana Parida,
Ranjan Kumar Jena
Publication year - 2012
Publication title -
international journal of computer science and informatics
Language(s) - English
Resource type - Journals
ISSN - 2231-5292
DOI - 10.47893/ijcsi.2012.1058
Subject(s) - image compression , computer science , jpeg 2000 , energy consumption , wireless sensor network , data compression , discrete wavelet transform , real time computing , image quality , set partitioning in hierarchical trees , transmission (telecommunications) , artificial intelligence , wavelet transform , wavelet , image processing , image (mathematics) , computer network , engineering , telecommunications , electrical engineering
When using wireless sensor networks for real-time data transmission, some critical points should be considered. Restricted computational power, memory limitations, narrow bandwidth and energy supplied present strong limits in sensor nodes. Therefore, maximizing network lifetime and minimizing energy consumption are always optimization goals. To reduce the energy consumption of the sensor network during image transmission, an energy efficient image compression scheme is proposed. The image compression scheme reduces the required memory. To address the above mentioned concerns, in this paper we describe an approach of image transmission in WSNs , taking advantage of JPEG2000 still image compression standard and using MATLAB . These features were achieved using techniques: the Discrete Wavelet Transform (DWT), and Embedded Block Coding with Optimized Truncation (EBCOT). Performance of the proposed image compression scheme is investigated with respect to image quality and energy consumption. Simulation results are presented and show that the proposed scheme optimizes network lifetime and reduces significantly the amount of required memory by analyzing the functional influence of each parameter of this distributed image compression algorithm.