1. Low Complexity Image Compression using Pruned 8-point DCT Approximation in Wireless Visual Sensor Networks
- Author
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Chaouki Araar, Mohammed Benmohammed, El-Bey Bourennane, Salim Ghanemi, Département d’informatique Université Badji-Mokhtar, Université Badji Mokhtar - Annaba [Annaba] (UBMA), Laboratoire d'Informatique Répartie [Algérie] (LIRE), Université de Constantine 2 Abdelhamid Mehri [Constantine], Laboratoire Electronique, Informatique et Image [UMR6306] (Le2i), Université de Bourgogne (UB)-École Nationale Supérieure d'Arts et Métiers (ENSAM), Arts et Métiers Sciences et Technologies, HESAM Université (HESAM)-HESAM Université (HESAM)-Arts et Métiers Sciences et Technologies, HESAM Université (HESAM)-HESAM Université (HESAM)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Centre National de la Recherche Scientifique (CNRS), Laboratoire d'Electronique, d'Informatique et d'Image [EA 7508] (Le2i), Université de Technologie de Belfort-Montbeliard (UTBM)-Université de Bourgogne (UB)-École Nationale Supérieure d'Arts et Métiers (ENSAM), Univ Ahmed Draia Adrar, Fac Sci & Technol, Dept Math & Comp Sci, IEEE, IEEE Algeria Sect, Grp Hamel, LADI, RedMed Grp, GMN, LEESI, université de Bourgogne, LE2I, Université de Bourgogne (UB)-Centre National de la Recherche Scientifique (CNRS)-École Nationale Supérieure d'Arts et Métiers (ENSAM), and HESAM Université (HESAM)-HESAM Université (HESAM)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement
- Subjects
Image quality ,Computer science ,Real-time computing ,Transform ,02 engineering and technology ,[MATH] Mathematics [math] ,low-complexity algorithms ,pruned 8-point DCT ,0202 electrical engineering, electronic engineering, information engineering ,Discrete cosine transform ,[MATH]Mathematics [math] ,Cosine ,Transform coding ,approximate DCT ,energy conservation ,020208 electrical & electronic engineering ,Energy consumption ,pruning approach ,[SPI.TRON] Engineering Sciences [physics]/Electronics ,image compression ,[SPI.TRON]Engineering Sciences [physics]/Electronics ,Uncompressed video ,WVSNs ,Discrete ,020201 artificial intelligence & image processing ,Wireless sensor network ,Data compression ,Image compression - Abstract
International audience; Since the transmission of the uncompressed image in the context of wireless visual sensor networks (WVSNs) consumes less energy than transmitting the compressed image, developing energy-aware compression algorithms are mandatory to extend the camera node's lifetime and thereby the whole network lifetime. The present paper studies a low-complexity image compression algorithm in the context of WVSNs. This algorithm consists of applying a pruning approach on a DCT approximation transform. The scheme is investigated in terms of computation cycles, processing time, energy consumption and image quality. Experimental works are conducted using the Atmel Atmega128 processor of Mica2 and MicaZ sensor boards. Simulation results show that the studied scheme can exhibit a competitive performance when compared against other algorithms. Furthermore, the scheme can achieve the best tradeoff between energy consumption and image quality.
- Published
- 2017