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correspond to the areas of the selected subbands independent from each
other as possible [21].
4.2.2 PROPOSED STEGANOGRAPHIC METHOD
The proposed color local complexity-estimation-based steganographic
(CLCES) method is described in this section. Figure (4.1) presents the
block diagram of the steps used in the proposed method [8].
FIGURE 4.1
Block diagram of the proposed CLCES method.
Step 1: Input the cover color image
We investigate the features of the
red, green, blue, (RGB); hue, saturation, value, (HSV); and luminance,
chromatic blue, chromatic red (YCbCr) color spaces in the proposed algo-
rithms to ensure that the visual artifacts appeared in the stego-images are
imperceptible, and the differences between the cover and the stego-images
are indistinguishable by the HVS [10, 11]. Given a RGB cover color im-
age, the HSV and YCbCr transformations are computed [22]. Then, from
each color space, we separate its color components in an independent way
and we apply in each component of the cover color image the next steps
of the proposed methods.
Stage A:
This stage improves the steganographic security and increas-
es the embedding capacity using the Step 2 [8]. The Step 2a is used to hide
data.
Step 2: Cover image preprocessing
The preprocessing imposes more
variation in pixel intensities of cover images compared to the original
ones. It has been proved in Reference [6] that the stego-images which car-
ried out the hiding of secret data in the cover images with more variation
in their pixel intensities are less detectable by the statistical steganalysis
increasing the embedding capacity [8]. Let propose a preprocessing step
in the wavelet domain using the advantages of the wavelet decomposi-
tion [8]. The fi rst-level Haar DWT and a redundancy of the approaches
algorithm are used [7, 23-25]. The preprocessing step is applied in the
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