Print ISSN: 1681-6900

Online ISSN: 2412-0758

Keywords : Wavelet Transform

A New Algorithm for a Steganography System

Atheer Alaa Sabri; Marwa Jaleel Mohsin

Engineering and Technology Journal, 2015, Volume 33, Issue 8, Pages 1955-1970

Steganography is the workmanship and study of concealing mystery information to provide a safe communication between two parties.This paper,displays othersteganographic algorithms for implanting encoded secretimagein grayscale and colorimages to give abnormal state security of information for correspondence over unsecured channels.The proposed algorithms first analyze the secret image using 1level -DWT and SLT respectively. It will be then encrypted the low frequency components of the secret image only using AES method and then embedded in the insensitive mid and high sub-bands gotten from the cover image in the wake of applying 2level- DWT and SLT on it, The embedding method used in this paper is LSB, the resulting image called stego-imageform different algorithms are then compared. .By using the proposed algorithms the capacity of the hidden secret data and stego image quality are improved. The embedding image reaches to half the size of cover image at same time PSNR reach to 62 dB and MSE about 0.36. The language used for testing the algorithms is MATLAB 2013a.

Principal Component Analysis Based Wavelet Transform

Hana; a M. Salman

Engineering and Technology Journal, 2012, Volume 30, Issue 9, Pages 1538-1549

The principal component analysis (PCA) is a valuable statistical means,
implemented in time domain that has found application in many fields such as face
recognition and image compression, and is a common technique for finding patterns in
data of high dimension. This paper investigates the ability to implement PCA in
frequency domain, by using the wavelet transform (WT), and evaluate its effectiveness
based on face recognition as a means to find patterns in data. The basic idea of
frequency domain implementation of the PCA refers to the correlation
implementation using wavelet transform.
The Min-max is invoked to increase wavelet based eigenface robustness to
variations in facial geometry and illumination. Two face images are contrast in terms
of their correlation distance. A threshold is used to restrict the impostor face image
from being identified. Experimental results point up the effectiveness of a new method
in either using varying (noisy images, unknown images, face expressions, illumine,
and scales ).

Channel Equalization Using Wavelet Denoising

M. H. Miry

Engineering and Technology Journal, 2007, Volume 25, Issue 9, Pages 1081-1091

A problem in digital signal transmission occurs when a signal in one
signal interval overlaps the signal in an adjacent interval. This problem is called
intersymbol interference and limits the speed of digital transmission. Interference
and noise are common in communication channels, and the recovery of
transmitted signals may be a difficult task. The adaptive equalizer which is used
to recover the transmitted signals and LMS algorithm which is one of the most
efficient criteria for determining the values of the adaptive equalizer coefficients
are very important in communication systems, but the LMS adaptive equalizer
suffers response degrades and slow convergence rate under low Signal-to- Noise
ratio (SNR) condition. The present work is concerned with the development and
application of wavelet transform based denoising technique for improving the
response and convergence rate of LMS adaptive equalizer in digital
communication systems under low SNR.