A Hybrid Approach for Simultaneous Compression and Encryption of an Image in Wireless Media Sensor Networks
In this paper, the advantages of discrete cosine transform and discrete wavelet transform have been harnessed by considering them together for compression, followed by an energy efficient Secured Force encryption technique. This was done in order to simul
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Abstract In this paper, the advantages of discrete cosine transform and discrete wavelet transform have been harnessed by considering them together for compression, followed by an energy efficient Secured Force encryption technique. This was done in order to simultaneously compress and encrypt the image that has to be transmitted through Wireless Media Sensor Network (WMSN). The proposed technique provides better and faster compression as compared to the existing techniques. Results show that, there is an average increase of 4 % in compression with respect to DCT based compression and DWT based compression. Also, in the proposed approach, Chroma cr. matrix is used for quantization, which has reduced the total processing time by a huge amount as compared to the other quantization matrices.
Keywords WMSN (wireless media sensor network) DCT (discrete cosine transform) DWT (discrete wavelet transform) SF (secure force) Compression Encryption
1 Introduction With the evolution of wireless sensor network (WSN) technology, the applications for which it was used initially, also diversified. In addition to transmit scalar data [1] such as temperature, humidity, rainfall, information etc. wireless sensor A. Karthikeyan (&) V. Srividhya P. Gupta N. Rai SENSE,VIT University, Vellore 632014, Tamil Nadu, India e-mail: [email protected] V. Srividhya e-mail: [email protected] P. Gupta e-mail: [email protected] N. Rai e-mail: [email protected] © Springer Science+Business Media Singapore 2016 R.K. Choudhary et al. (eds.), Advanced Computing and Communication Technologies, Advances in Intelligent Systems and Computing 452, DOI 10.1007/978-981-10-1023-1_47
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networks are nowadays used for transmitting and receiving multimedia messages such as images, videos etc. The multimedia applications have led to the introduction of wireless multimedia sensor networks (WMSN) [1] which differs from WSN in terms of memory, processing power, and architecture [2]. Although, the concept of wireless technology remains the same but, the algorithms used for processing information are different from wireless sensor network. Though, WMSN has a huge advantage over WSN in terms of amount of data that can be transferred but, there are certain limitations that hinder the performance of WMSN’s such as, large memory consumption, high processing time and unreliable transmission. Since, wireless media sensor node deals with the images, most of the memory consumed is because of allocation of space to each and every pixel. As the image is composed of many pixels, there is a possibility that at some places, there is a little variation in the definition of pixels which, indicates a lot of redundant information. There are generally three types of redundancies (1) Spatial Redundancy: Where there is less variation in adjacent pixels, (2) Temporal Redundancy: Here we are concerned with number of bits required to represent given image and, (3) Spectral Redundancy: Where there is a correla
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