STEGANOGRAPHIC METHOD FOR COLOR IMAGES USING VARIANCE FIELD ESTIMATION AND SCALING FACTOR FOR ENERGY CONSERVATION - Theoretical and Computational Research in the 21st Century - page 97

Step 6: Inverse discrete wavelet transform (IDWT) computation We
obtain the resulted stego-image applying the IDWT to the wavelet coef-
fi cients of the stego-image (Figure 4.1).

4.3 RESULTS AND DISCUSSION

The purpose of this research is to propose a simple steganographic algo-
rithm implementation, with little resource consumption on mobile devic-
es, where the results were qualitative, quantitative, and highly acceptable
steganalysis. The purpose of steganography is to insert hidden information
on a digital file, thus achieving high resource utilization. We present the
results better PSNR, MAE, CC, and Q for a scaling factor when j = 9.
Through analysis of steganalysis is determined the probability of detection
of hidden information exceeds 95 percent, higher than results reported in
classical literature.
The proposed CLCES method is evaluated [8], and its performance
is compared with the LSB [33] steganographic method. We also adapt
the LSB method [33] to work in the wavelet domain using the second-
level Daubechies db4 DWT to compare our proposal, in here this method
is named as WLSB. The image quality of various schemes is compared
in terms of the peak signal-to-noise ratio (PSNR); the mean absolute er-
ror (MAE); the normalized color difference (NCD); the cross-correlation
(CC); the quality index (Q); and the hiding capacity (HC) criteria [1, 4, 5,
7, 25, 33, 34, 35].
In our experiments, we use the 320 × 320 color images “Lena” and
“Mandrill,” and we present the results of several steganographic methods
for the RGB, HSV, and YCbCr color spaces. The performance results for
the stego-image “Mandrill” (the secret image “Lena”) and the retrieved
secret image “Lena” are shown in Tables (4.1) and (4.2), respectively.

TABLE 4.1 Performance results for the stego-image “Mandrill” with the secret image

“Lena”

Criteria for the RGB color space

Algorithms

PSNR dB MAE CC Q NCD HC (Kb)

LSB 34.5602 3.5758 0.9978 0.9977 7.3506e-4 1.9199e3

WLSB 28.8347 8.8469 0.9977 0.9963 0.0053 0.8352e3

CLCES ( βs 1 ) 38.2650 1.4503 0.9983 0.9984 2.5473e-4 1.9183e3