Print ISSN: 1681-6900

Online ISSN: 2412-0758

Keywords : wavelet


A Simple Hybrid Scheme for Denoisin the Medical Ultrasound Images

Nedhal Kareem; Yasmin Abdul Ghani; Mais Abid Khalil

Engineering and Technology Journal, 2013, Volume 31, Issue 3, Pages 357-367

The medical ultrasound images are usually corrupted by type of noise called ‘speckle’. This noise is caused by the coherent nature of the scattering phenomenon. There are many filters used to reduce the effect of speckle noise like mean, median, Lee, Kaun, Gamma, Weiner, Frost. Recently, One of the most commonly speckle denoising filter is wavelet filter.
In this paper, A simple hybrid scheme is suggest to denosing the ultrasound images. this scheme consist from two interacted filter (winner and mean filter) with window size 3*3 and designed simple adaptive filter(SAF). The adaptation of SAF depends on nonlinear gain function. In order to test the efficiency of the suggested scheme, its performance was compared with performance of other filters like mean, wiener, and wavelet filter

Design of Hierarchical Architecture of Multilevel Discrete Wavelet Transform Using VHDL Language

Waleed Fawwaz Shareef

Engineering and Technology Journal, 2010, Volume 28, Issue 7, Pages 1350-1360

The wide spread of devices that use image processing in its
functions, like cellular phone and digital cameras, increases the need for
specialized processors for these functions as a replacement for software
programs that consume more time and resources. This paper presents a
hardware description for discrete wavelet transform (DWT) module in
VHDL language. The design involves the forward DWT (fDWT) and its
inverse (iDWT) characterized by variable number of transformation levels,
ranging from one level to seven levels. Each one of these two modules is
designed as hierarchical scheme that uses one-dimensional processing
module twice to represent two-dimensional processing. The module can be
used repeatedly on the same image for multilevel processing. Three
versions of the design are presented (v64, v128 and v256), each one
adapted different image size. Synthesis process showed that the design
frequency is about 56MHz. The simulation process showed that the
maximum possible rounding error is about 0.012%. This resolution with the
variable number of processing level adapts this design to fit in many
applications. Finally, a comparison of the proposed design with other
related work is presented, considering performance and specifications.

Palmprint Characterization Using Multi-wavelet Transform for Human Identification

Hana; a M. Salman

Engineering and Technology Journal, 2009, Volume 27, Issue 3, Pages 405-417

The human hand presents the source for a numerous of physiological biometric
features, from these are palmprint, hand geometry, finger geometry and the vein pattern on
the dorsum of the hand, are mostly used in many fields for different applications. Lines and
points are extracted from palms for individual identification in original image or frequency
space. In this paper, a preprocessing to extract the central part from the input palmprint
image, next a 2-D multi-wavelet transform is used to convert the palmprint image into 16
sub-bands, and the texture feature vectors, energy and entropy for each of the 16 sub-bands
is computed and normalized with min-max method for individual identification. The
correlation distance is used as a similarity measure. The experimental results point up the
effectiveness of a method in either using low resolution or noisy images