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ISSN-2349-1841(Online)
Volume 1, Issue 2, March 2015
International Journal of Research Development
& Innovation (IJRDI)
Research Paper
Available online at: www.ijrdi.com
Review On:-Designing an Efficient Image
Encryption-Then-Compression System with
HAAR and SYMLET Wavelet
Nivedita #1, Sanjay Yadav*2
SIEET Sunder Nagar,Mandi
1
nivedita867@gmail.com
*
Assistant Professor
SIEET Sunder Nagar,Mandi
2
sanjay12066@yahoo.com ,samjess.jess@gmail.com
Abstract:- Images can be encrypted in many ways
and several techniques have used different
encryption methods. In this research we apply a
new modified International HAAR and SYMLET
Wavelet with Data Encryption Algorithm. It is
used to encrypt the full image in an efficient
secure manner. After encryption the original file
will be compressed and we get compressed image.
To provide a reasonably security the proposed
image encryption method is operated in the
prediction error domain. It also demonstrates
arithmetic coding-based approach which can be
exploited to efficiently compress the encrypted
images and most of the existing ETC solutions
induce significant penalty on the compression
efficiency. By using HAAR and SYMLET wavelet
transform with ETC there is better compression
efficiency. For the implementation of this
proposed work we use the Image Processing
Toolbox under MATLAB software.
Keywords:- Compression of Encrypted image,
HAAR Wavelet and SYMLET Wavelet
I. INTRODUCTION
With the fast growing in network and multimedia
technologies the security of multimedia becomes
more important. Since multimedia information is
transmitted over open networks more frequently.
Typically; the reliable security is necessary to data
protection of digital figures and videos. Encryption
techniques for multimedia information need to be
specifically designed to save multimedia
information and fulfill the security need for a
particular multimedia application. For example the
real-time encryption of an entire video stream using
classical ciphers which needs heavy computation
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due to the more amounts of data involved. But
many multimedia applications require security to a
lower level and this can be gained using selective
encryption that leaves some perceptual message
after encryption. Therefore Government and
military and private business amass great deal of
confidential figures. Most of information is
collected and stored on electronic computers and
transmitted across network to the other computer. If
the confidential figures about enemy positions and
patient and geographical areas goes to the wrong
hands than such a breach of security could lead to
more wars and wrong treatment etc. Protecting
confidential figures is the legal requirement and
ethical requirement. It stores data in the form of
files in computer system. For keeping the
information the file is taken as a basic entity. It is
worldwide accepted fact that securing file data is
very important in today’s computing environment.
Best encryption makes a source look completely
random; traditional algorithms are unable to
compress encrypted data. To this reason, traditional
systems make sure to compress before they
encrypt. Here using the concept of public key
encryption for the encryption and decryption of
image. In this public key’s of sender and receiver is
known to both but private key’s are kept secret.
Nor the security and the compression efficiency
will be sacrificed by performing compression in the
encrypted domain.
The processing encrypted data directly in the
encrypted domain has been receiving increasing
attention in recent years. At the first glance this
seems to be infeasible for Charlie to compress the
encrypted information. Since no signal structure
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International Journal of Research Development & Innovation (IJRDI)
Volume 1, Issue 2, March 2015, Pg. 63-66
can be exploited to enable a traditional compressor.
Although counter-intuitive Johnson showed that the
stream cipher encrypted data is compressible by the
use of coding with side information principles
without compromising the compression efficiency
or the information-theoretic security. In addition to
the theoretical finding; and invented practical
algorithms to lossless compress the encrypted
binary figures. Lazaretto and Barni presented
several methods for lossless compression of
encrypted gray scale/colour images by applying
LDPC codes in various bit-planes and exploiting
the inter / intra correlation.
II. HAAR WAVELET
The HAAR wavelet is a certain sequence of
functions. HAAR is used to give an example of a
countable Orthonormal system for the space of
square integrable functions on the real line by using
these functions. Therefore study of wavelets and
even the term "wavelet" did not come until much
later. Thus HAAR wavelet is easiest and simplest
possible wavelet. Therefore technical disadvantage
of this wavelet is that:
 it is not continuous and
 It is not differentiable.
wavelet transform is not Fourier-based and
therefore wavelets do a better job of handling
discontinuities in data in the discrete cosine
transform. By calculating the sums and differences
of adjacent elements the HAAR wavelet operates
on information. Then it operates first on adjacent
horizontal elements and then on adjacent vertical
elements.
Therefore HAAR transform is
computed using:
…(3)
III.
SYMLET WAVELET
SYMLET wavelets are also a family of wavelets.
Wavelets are a modified version of SYMLET
wavelets with increased symmetry. SYMLETs are
also compactly and orthogonal supported wavelets
which are proposed by ‘I’. SYMLET as
medications to the Daubechies family. SYMLETs
have the least asymmetry and are near symmetric.
In SYMLETs the associated scaling ﬁlters are near
linear-phase ﬁlters. The properties of SYMLETs
are nearly the same as those of the Daubechies
wavelets. The scaling functions and SYMLET
wavelet for orders are shown in below figure:
Figure 1: HAAR wavelet window
The HAAR wavelet's mother wavelet function ψ (t)
can be described as:
𝟏 𝟎≤𝐭≤
𝛗(𝐭) = { −𝟏
𝟎
𝟏
𝟐
𝟏
𝟐
≤𝐭≤𝟏
… (1)
𝐨𝐭𝐡𝐞𝐫𝐰𝐢𝐬𝐞
And its scaling function φ (t) can be described as:
𝟏 𝟎≤𝐭≤𝟏
∅(𝐭) = {
… (2)
𝟎 𝐨𝐭𝐡𝐞𝐫𝐰𝐬𝐞
The Wavelets are mathematical functions that were
developed by scientists working in several different
fields for the purpose of sorting data by frequency.
And translated information can be sorted at a
resolution which matches its scale and studying
data at different levels allows for the development
of a more complete picture. All features that are
small features and large features are discernable
because they are studied differently. Thus the
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Figure 2: SYMLET wavelet
The SYMLET wavelets are also known as
SYMLET
least-asymmetric
wavelets.
The
SYMLETs are more symmetric than the extremely
phase wavelets. Where N is the number of
vanishing moments. These filters are also referred
to the number of filter taps which is 2N and enter
the wave info ('sym') as the MATLAB command to
obtain a survey of the main properties of this
family.
IV. PREVIOUS WORK
S. Dharanidharan AP/CSE, S. B. Manoj Kumar
in 2013. He proposed Modified the International
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International Journal of Research Development & Innovation (IJRDI)
Volume 1, Issue 2, March 2015, Pg. 63-66
Data Encryption Algorithm using in Image
Compression Techniques. Images can be encrypted
in many ways and several techniques have used
different encryption methods. In this research he
applied a new modified the International Data
Encryption Algorithm to encrypt the full image in
an efficient secure manner. After encryption the
original file will be segmented and then converted
to another image files. The segmented image files
are merged by using Huffman Algorithm. And it
merges the entire segmented image and compress
into a single image. Thus it retrieves a fully
decrypted image. It finds an efficient way to
transfer the encrypted images to multipath routing
techniques. The above compressed image has been
sent to the single path way and now it enhanced
with the multipath routing algorithm and finally it
get an efficient transmission and reliable and
efficient image.
Ch. Samson V. U. K. Sastry in 2012. He
proposed an RGB Image Encryption which is
supported
by
Wavelet-based
Lossless
Compression. This paper proposed a method for an
RGB image encryption supported by lifting scheme
based lossless compression. In this paper he
compressed the input color image using a 2-D
integer wavelet transform. Then to achieve
additional compression he applied lossless
predictive coding. Then the compressed image was
encrypted by using Secure Advanced Hill Cipher
(SAHC) involving a pair of involuntary matrices a
function called Mix () and an operation called
XOR. After that decryption followed by
reconstruction that shows there is no difference
between the output image and the input image. The
proposed method is used for efficient and secure
transmission of image data and for better results.
Shaimaa A. El-said Khalid F. A. Hussein
Mohamed M. Fouad in 2010. He proposed
Securing Image Transmission
by Using
Compression
Encryption
Technique.
The
Multimedia is one of the most popular data shared
in the Web and the protection of it via encryption
techniques. This paper presented a secure and
computationally
feasible
Algorithm
called
Optimized Multiple Huffman Tables (OMHT)
technique. Optimized Multiple Huffman Tables
(OMHT) depends on the statistical-model-based
compression method to generate different tables
from the same data type of images or videos to be
encrypted leading to increase compression
efficiency and security of the used tables. The
resulting system can provide superior or better
performance over other techniques by both its
generic encryption and its simple adaptation to
multimedia in terms of a joint consideration of
security and bit rate overhead. The effectiveness
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and robustness of this method was verified by
measuring its security strength and comparing its
computational cost against other techniques. The
proposed technique guaranteed security and
fastness without noticeable increase in encoded
image size.
V. PROPOSED WORK
Phase 1:
Develop an opening GUI for this implementation.
After that code is developed f o r t h e l o a d i n g
the image file in the MATLAB
database.
Phase 2:
Develop a code for Image Compression Using
HAAR and SYMLET Wavelet Transform.
Phase 3:
Develop a code for encryption algorithm with
suitable key. Finally HAAR and SYMLET
wavelet transform with encryption algorithm are
applied on the input image.
Phase 4:
Analysis of result obtained is done on the basis of
various parameters like Compression Ratio, MSE,
BER and PSNR.
VI. CONCLUSION
To proposed an Efficient Image Encryption-ThenCompression System with HAAR and SYMLET
Wavelet Transform then encrypt image using
pseudo random permutation. In this method the
pixel values are same after encryption but their
position will be changed. The image obtained is
nearly similar to the original image due to high
correlation between the adjacent pixels. Many
Image Compression techniques have been proposed
earlier but they were not secure enough and
compression ratio is poor. Image Compression
could not provide better results as technique used
for Compression with SYMLET wavelet alone was
not good enough. Therefore HAAR wavelet used
with SYMLET wavelet for data compression. And
propose an Efficient Image Encryption-ThenCompression System with HAAR and SYMLET
Wavelet Transform.
ACKNOWLEDGEMENT
Thanks to my Guide and family member who
always support, help and guide me during my
dissertation. Special thanks to my father who
always support my innovative ideas.
REFERENCES
[1] R. C. Gonzalez and R. E. Woods, Digital Image
Processing 2/E. Upper Saddle River, NJ: PrenticeHall, 2002.
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International Journal of Research Development & Innovation (IJRDI)
Volume 1, Issue 2, March 2015, Pg. 63-66
[2] J. J. Ding and J. D. Huang, “Image
Compression by Segmentation and Boundary
Description,” June, 2008.
[9] Mitra, Y. V. Subba Rao, S. R. M. Prasanna, “A
New Image Encryption Approach using
Combinational Permutation Techniques”
[3] G. K. Wallace, 'The JPEG Still Picture
Compression Standard', Communications of the
ACM, Vol. 34, Issue 4, pp.30-44.
[10] Xinpeng Zhang, “Lossy Compression and
Iterative Reconstruction for Encrypted Image”
IEEE transactions on information forensics and
security, vol. 6, no. 1, march 2011.
[4] M. Campista, P. Esposito, I. Moraes, L. H.
Costa, O. C. Duarte, D. Passos, C. V. de
Albuquerque, D. C. Saade, and M. Rubinstein,
outing metrics and protocols for wireless mesh
networks, IEEE Netw., vol. 22, no. 1, pp. 6–12,
Jan.–Feb. 2008.
[11] Daniel Schonberg, Stark C. Draper, Chuohao
Yeo,
Kannan
Ramchandran,
“Towards
Compression of Encrypted Images and Video
Sequences”
[5] N. C. Fernandes, M. D. D. Moreira, and O. C.
M. B. Duarte, ―An efficient filter-based
addressing protocol for auto configuration of
mobile ad hoc networks,‖ in Proc. IEEE
INFOCOM, Apr. 2009, pp.2464–2472.
[6] P. B. Velloso, R. P. Laufer, O. C.M. B. Duarte,
and G. Pujolle, ―Trust management in mobile ad
hoc networks using a scalable maturity based
model, IEEE Trans. Netw. Service Manage. vol. 7,
no. 3, pp. 172–185, Sep. 2010.
[7] D. Passos and C. V. N. Albuquerque, ―A joint
approach to routing metrics and rate adaptation in
wireless mesh networks, in Proc. IEEE INFOCOM
Workshops, Apr. 2009, pp. 1–2.
[8] S. Biswas and R. Morris, ―ExOR:
Opportunistic multi-hop routing for wireless
networks, ‖ in Proc. ACM SIGCOMM, Aug.
2005, pp. 133–143.
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[12] Ibrahim Fathy El-Ashry, “Digital Image
Encryption” A Thesis Submitted for The Degree of
M. Sc. of Communications Engineering.
[13] D. Schonberg, S. C. Draper, C. Yeo, K.
Ramchandran, “Toward compression of encrypted
images and video sequences” IEEE Trans. Inf.
Forensics Security, vol. 3, no. 4, pp. 749–762, Dec.
2008.
[14] D. Slepian and J. K. Wolf, “Noiseless coding
of correlated information sources,” IEEE Trans.
Inform. Theory, vol. IT-19, pp. 471–480, July
1973.
[15] A.Wyner and J. Ziv, “The rate-distortion
function for source coding withcside information at
the decoder,” IEEE Trans. Inform. Theory, vol. IT22, cpp. 1–10, Jan. 1976.
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