Information Technology Reference
In-Depth Information
4.1 INTRODUCTION
Steganography involves the secret data communications in an appropriate
multimedia carrier (i.e. audio, image, and video files), under the assump-
tion that if the secret data is visible, the point of attack is evident [1, 3];
thus, the goal here is to conceal the existence of the embedded data. In the
case of image files, a steganographic method employs innocent-looking
media called host or cover image to imperceptibly carry hidden data to an
intended recipient [1-3]. The image embedded with the hidden data (i.e.,
secret data, copyright notice, and serial number) is called the stego-image
and it looks as a normal image. The steganalysis techniques detect the ex-
istence of secret data in digital media, and these techniques are designed
to distinguish between the cover and stego-images [4, 5].
Steganographic techniques can be classifi ed into spatial, frequency,
and adaptive methods [1]. The
spatial methods
generally use a technique
to replace the direct least signifi cant bit (LSB) substituting a redundant
part of a cover image with a secret message. The
methods based in
fre-
quency domain
, such as the Fourier transform (FT), the discrete cosine
transform (DCT), and the discrete wavelet transform (DWT) embed secret
information in the frequency domain of a cover image. These methods
hide messages in signifi cant areas of the cover image which makes them
more robust to attacks, such as compression, cropping, and some image
processing, than the LSB approach [1]. Recently, there exist methods such
as perceptual masking (PM) or adaptive steganography (AS), which can
be applied in the spatial or frequency domain [1].
In this chapter, we present a wavelet steganographic scheme. The pro-
posed method is capable of preventing visual degradation and providing a
large embedding capacity. A wavelet domain preprocessing step is intro-
duced before applying the proposed scheme to improve the steganography
security [6, 7]. The embedding capacity for each pixel is determined by
the local complexity of the cover image, allowing good visual quality as
well as embedding a large amount of secret messages. These pixels are
classifi ed using a threshold based on the standard deviation of the local
complexity of the cover image [7, 8]. Experimental results demonstrated
that the proposed steganographic algorithm produces insignifi cant visual
distortion because of the hidden message and provides high embedding
capacity superior to that offered by the existing schemes. The proposed
method is a secure steganographic algorithm due it can resist the image
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