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Energy conserving texture‐based adaptable compressive sensing scheme for WVSN
Author(s) -
Subbu Lakshmi T.C.,
Gnanadurai D.,
Muthulakshmi I.
Publication year - 2019
Publication title -
concurrency and computation: practice and experience
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.309
H-Index - 67
eISSN - 1532-0634
pISSN - 1532-0626
DOI - 10.1002/cpe.5178
Subject(s) - computer science , compressed sensing , wireless sensor network , energy consumption , property (philosophy) , energy (signal processing) , texture (cosmology) , efficient energy use , scheme (mathematics) , wireless , real time computing , artificial intelligence , computer network , image (mathematics) , telecommunications , engineering , electrical engineering , mathematical analysis , philosophy , statistics , mathematics , epistemology
Summary Wireless Sensor Networks (WSN) have gained considerable research interest due to its wider applicability and efficiency. Due to the technological advancement, the WSN is multifaceted and one of the facets is the Wireless Visual Sensor Network (WVSN). The core functionality of WVSN is to handle multimedia data that involves data processing and transference, which, in turn, consumes more energy. Data transference requires more energy and the energy consumption is reduced by the concept of compressive sensing. Understanding the benefits of compressive sensing, this article proposes an adaptable compressive scheme that relies on the texture property of the video frames. The texture property is extracted by means of Local Directional Pattern (LDP). The performance of the proposed approach is evaluated in terms of image quality, time, and energy consumption. The proposed approach outperforms the comparative approaches with reasonable performance.