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AN EFFICIENT COLOR IMAGE ENCRYPTION ANDLOSSLESS COMPRESSION SYSTEM USING SPIHT

ARITHMETIC ENCODER

M Ranganayaki1*, Nithya Jeevanand1 and W Nancy1

*Corresponding Author: M Ranganayaki,mranganayaki@jeppiaarinstitute.org

This paper presents a novel watermarking mechanism for digital media that embeds arecognizable pattern into the spatial domain and an invisible image into the frequency domain.Undoubtedly, visible watermarking is important for protecting online resources from unauthorizedreproduction. Lossless compression of encrypted sources can be achieved through SPIHTcoding. For encrypted real-world sources, such as images, the key to improve the compressionefficiency is how the source dependency is exploited. Lossless compression of encrypted colorimages can be achieved through arithmetic encoder. For encrypted real-world sources, suchas images, the key to improve the compression efficiency is how the source dependency isexploited. This is color image encryption method where image is encrypted by specific rule thatis rearrangement of image pixels. In this paper, we present color Image encryption and decryptionby using partition and scanning pattern which is related to scan approach.

Keywords: Encrypted color images, SPIHT coding lossless compression, Image encryptionand decryption

INTRODUCTIONEncryption is used to securely transmit data inopen networks. Each type of data has its ownfeatures; therefore different techniques shouldbe used to protect confidential image datafrom unauthorized access. Most of theavailable encryption algorithms are mainlyused for textual data and may not be suitablefor multimedia data such as images. Forsecure transmission, various compression and

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Int. J. Elec&Electr.Eng&Telecoms. 2015

1 Department of Electronics and Communication Engineering, Jeppiaar Institute of Technology.

encryption techniques are proposed to satisfya fast and secure transmission. However thesetwo techniques must be studied separately. Inthis paper we propose a method combiningencryption and compression based enhancedencryption and compression algorithms.

PROBLEM STATEMENTThe proposed algorithm uses binary codesand pixels inside an image. The file is used

Research Paper

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before it is converted to binary codes tomaximize the storage of data inside the image.The system is then tested to see the viabilityof the existing algorithm. Various sizes of dataare stored inside the images and the PSNR(Peak signal-to-noise ratio) is also capturedfor each of the images tested. Based on thePSNR value of each images, the image has ahigher PSNR value.

METHODOLOGYThe algorithms proposed are:

Algorithm 1: (Image hiding – watermarking)

It is accomplished by using Inter blockcorrelation side match vector quantization.

Algorithm 2: (Image Compression)

Image Compression is done by usingSPIHT algorithm.

Image Hiding – Inter BlockCorrelation Side Match VectorQuantizationSince Inter Block Correlation Side MatchVector Quantization (IBCSMVQ) providesbetter image quality of reconstructed imageand compression bit rate than Side MatchVector Quantization (SMVQ) does, it becomesanother choice to compress the transmittingimages when the bandwidth is limited. Toexpand the cover media for transmittingconfidential information, we propose a noveldata hiding scheme which embeds secret datainto the IBCSMVQ-compressed image. Interms of the payload capacity, the visual quality,and the compression rate, experimental resultsconfirm that the performances of our schemeare better than that of other information hidingschemes for SMVQ-based and IBCSMVQ-based compressed images. In addition, theembedded secret data can be extracted fromthe stego-image without referencing theoriginal cover image.

Image CompressionThe traditional image coding technology usesthe redundant data in an image to compressit. But these methods have been replaced bydigital wavelet transform based compressionmethod as these methods have high speed,low memory requirements and completereversibility. Now in this work we areconsidering SPIHT as a placement for waveletcompression methods. We are comparing itwith wavelet encoding scheme and comparingthe final results in terms of bit error rate, PSNRand MSE.

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Figure 1: ResultsFigure 1 (Cont.)

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Int. J. Elec&Electr.Eng&Telecoms. 2015 M Ranganayaki et al., 2015

Figure 1 (Cont.)

DISCUSSIONS ANDCONCLUSIONModern image hiding studies the encodingand the detection of secret messagestransmitted over digital communicationplatforms. Image hiding methods hide thepresence of an arbitrary digital message byencoding it into other digital media, thusmaking its discovery by potential investigatorsvery difficult. The importance of image hidingwas recently reconsidered by governmentswith regard to Internet security.

Still the quality of the image remains sameafter the compression.

REFERENCES1. Announcing the Advanced Encryption

Standard (AES), National Institute ofStandards & Technology, November,Gaithersburg, MD, USA.

2. Gersho A and Gray R M (1992), VectorQuantization and Signal Compression,Kluwer, Norwell, MA, USA.

3. Nasrabadi N M and King R (1988),“Image Coding Using Vector Quantization:A Review”, IEEE Trans. Commun.,Vol. 36, No. 8, pp. 957-971.

4. Pennebaker W B and Mitchell J L (1993),The JPEG Still Image Data CompressionStandard, New York, USA.

5. Taubman D S and Marcellin M W (2002),JPEG2000: Image CompressionFundamentals Standards and Practice,Kluwer, Norwell, MA, USA.