scholarly journals A Low Power Shift Add Multiplier for Lifting Based Dwt using Kogge Stone Adder

2020 ◽  
Vol 9 (4) ◽  
pp. 1080-1086
Author(s):  
A. Akilandeswari ◽  
◽  
Annie Grace Vimala ◽  
D. Sungeetha ◽  
◽  
...  
Keyword(s):  
The Other ◽  
Discrete Wavelet ◽  
Limited Memory ◽  
Power Shift ◽  
Multi Resolution Analysis ◽  
Suggested Technique ◽  
Field Programmable ◽  
Resolution Analysis ◽  
Common Technique

The most common technique used for image processing applications is ‘The wavelet transformation’. The Discrete Wavelet Transform (DWT) keeps the time as well as frequency information depend on a multi resolution analysis structure, where the other classical transforms like Fast Fourier Transform (FFT), Discrete Cosine Transform (DCT) will not do that. Because of this feature, the quality of the repaired image is improved when comparing to the other transforms. To implement the DWT on a real time codec, a fast device needs to be targeted. While comparing with the other implementation such as PCs, ARM processors, DSPs etc, Field Programmable Gate Array (FPGA) implementation of DWT had better processing speed and costs were vey less. A Fast Architecture based DWT using Kogge Stone Adder is proposed in this paper where the coefficients of lifting scheme are calculated by using Shift adder and Kogge Stone Adder where other techniques used multiplier. The most important intention of the suggested technique is to use minimum calculation and limited memory. The simulation of the suggested design is dole out on the Xilinx 14.1 style tool and also the performance is evaluated and compared with the present architectures.

scholarly journals A Low Power Shift Add Multiplier for Lifting Based Dwt using Kogge Stone Adder

2020 ◽  
Vol 9 (4) ◽  
pp. 1080-1086
Keyword(s):  
The Other ◽  
Discrete Wavelet ◽  
Limited Memory ◽  
Power Shift ◽  
Multi Resolution Analysis ◽  
Suggested Technique ◽  
Field Programmable ◽  
Resolution Analysis ◽  
Common Technique

The most common technique used for image processing applications is ‘The wavelet transformation’. The Discrete Wavelet Transform (DWT) keeps the time as well as frequency information depend on a multi resolution analysis structure, where the other classical transforms like Fast Fourier Transform (FFT), Discrete Cosine Transform (DCT) will not do that. Because of this feature, the quality of the repaired image is improved when comparing to the other transforms. To implement the DWT on a real time codec, a fast device needs to be targeted. While comparing with the other implementation such as PCs, ARM processors, DSPs etc, Field Programmable Gate Array (FPGA) implementation of DWT had better processing speed and costs were vey less. A Fast Architecture based DWT using Kogge Stone Adder is proposed in this paper where the coefficients of lifting scheme are calculated by using Shift adder and Kogge Stone Adder where other techniques used multiplier. The most important intention of the suggested technique is to use minimum calculation and limited memory. The simulation of the suggested design is dole out on the Xilinx 14.1 style tool and also the performance is evaluated and compared with the present architectures.

Coal Gangue Image Edge Detection Based on Wavelet Transform

2012 ◽  
Vol 214 ◽  
pp. 375-380 ◽  
Author(s):  
Tie Yun Li
Keyword(s):  
Wavelet Transform ◽  
Edge Detection ◽  
Detection Algorithm ◽  
Coal Gangue ◽  
Edge Detection Algorithm ◽  
Image Edge Detection ◽  
Multi Resolution Analysis ◽  
Resolution Analysis ◽  
Image Edge

An edge detection algorithm is developed for coal gangue images, and the method has two advantages compared with traditional ones. Firstly, multi-resolution analysis of wavelet transform can improve the quality of edge detection. Secondly, the algorithm is faster for real time. Since the threshold directly from the coefficients of wavelet transform, the rate of recognition for coal gangue is highly raised. The experiment results show that the method is an efficient edge detection algorithm for extraction edges from the noised images of coal gangues.

A New Approach for Classification of Fault in Transmission Line with Combination of Wavelet Multi Resolution Analysis and Neural Networks

2017 ◽  
Vol 8 (1) ◽  
pp. 505
Author(s):  
Y Srinivasa Rao ◽  
G. Ravi Kumar ◽  
G. Kesava Rao
Keyword(s):  
Neural Networks ◽  
Wavelet Transform ◽  
Transmission Line ◽  
Discrete Wavelet Transform ◽  
Discrete Wavelet ◽  
New Approach ◽  
The Neural Network ◽  
Multi Resolution Analysis ◽  
Resolution Analysis

An appropriate fault detection and classification of power system transmission line using discrete wavelet transform and artificial neural networks is performed in this paper. The analysis is carried out by applying discrete wavelet transform for obtained fault phase currents. The work represented in this paper are mainly concentrated on classification of fault and this classification is done based on the obtained energy values after applying discrete wavelet transform by taking this values as an input for the neural network. The proposed system and analysis is carried out in Matlab Simulink.

Multi-Resolution Analysis of the Acousto-Ultrasonic Testing Signal for Composite Material Detection

2011 ◽  
Vol 65 ◽  
pp. 108-112
Author(s):  
Bin Jing ◽  
Chunan Ai ◽  
Yu Liu
Keyword(s):  
Adaptive Filtering ◽  
Characteristic Frequency ◽  
Composite Shell ◽  
Bond Quality ◽  
Multi Resolution Analysis ◽  
Material Detection ◽  
Resolution Analysis ◽  
Testing Signal ◽  
Stress Wave Factor

The AU technique is employed in this paper to test the specimen which is made up of composite shell and adiabatic layer; the noise in the tested signal is reduced by adaptive filtering; Multi-resolution analysis of the signal is achieved by wavelet transform. By comparing the ratio of the energy of signal in different frequency zones to the total energy, the characteristic frequency zone of the signal is gained. The characteristic frequency zone of the signal from specimen is evaluated by energy integral Stress Wave Factor (SWF). Flaws are found effectively, and the size of flaw can be evaluated qualitatively. The validity of AU test for bond quality of the structure is approved in the experiments.

Wavelet analysis on developable surface base on area preserving projection

2015 ◽  
Vol 13 (01) ◽  
pp. 1550007 ◽  
Author(s):  
Bao Qin Wang ◽  
Gang Wang ◽  
Xiao Hui Zhou ◽  
Yu Su
Keyword(s):  
Wavelet Transform ◽  
Discrete Wavelet Transform ◽  
Scaling Function ◽  
Discrete Wavelet ◽  
Developable Surface ◽  
Simple Method ◽  
Multi Resolution Analysis ◽  
Resolution Analysis ◽  
Area Preserving ◽  
The Scaling Function

In this paper, a simple method is given in order to construct an area preserving mapping from a developable surface M to a plane. Based on the area preserving projection, we give some important formulas on M, and define a multi-resolution analysis on L2(M). We provide the conditions to further discuss the continuous wavelet transform and discrete wavelet transform on developable surface. At the same time, we derived two-scale equations that the scaling function and wavelet function on developable surface satisfied, we also define and discuss the orthogonality, and several important theorems are given. Finally, we construct the numerical examples. The focus of this paper is the area preserving mapping that from developable surface M to a plane, and the discrete wavelet transform on developable surface.

scholarly journals ANALYSIS OF EFFECTS OF USING 9/7 WAVELET COEFFICIENTS IN MULTI-RESOLUTION ANALYSIS

2016 ◽  
Vol 2 (1) ◽  
Author(s):  
Manish Sharma ◽  
Prof. Sonu Lal
Keyword(s):  
High Speed ◽  
Utilization Efficiency ◽  
Parallel Structure ◽  
Discrete Wavelet ◽  
Distributed Arithmetic ◽  
Fpga Design ◽  
Multi Resolution Analysis ◽  
Field Programmable ◽  
On Chip ◽  
Area Efficient

Conventional distributed arithmetic (DA) is popular in field programmable gate array (FPGA) design, and it features on-chip ROM to achieve high speed and regularity. In this paper, we describe high speed area efficient 1-D discrete wavelet transform (DWT) using 9/7 filter based new efficient distributed arithmetic (NEDA) Technique. Being area efficient architecture free of ROM, multiplication, and subtraction, NEDA can also expose the redundancy existing in the adder array consisting of entries of 0 and 1. This architecture supports any size of image pixel value and any level of decomposition. The parallel structure has 100% hardware utilization efficiency.

TEXTURE CHARACTERIZATION USING WSFS AND WCFS

2009 ◽  
Vol 09 (01) ◽  
pp. 77-100
Author(s):  
S. ARIVAZHAGAN ◽  
L. GANESAN
Keyword(s):  
Texture Analysis ◽  
Image Data ◽  
Discrete Wavelet ◽  
Statistical Features ◽  
Main Difficulty ◽  
Data Bases ◽  
The Past ◽  
Multi Resolution Analysis ◽  
Resolution Analysis ◽  
Texture Characterization

Texture analysis plays an important role in many tasks, ranging from remote sensing to medical imaging and query by content in large image data bases. The main difficulty of texture analysis in the past was the lack of adequate tools to characterize different scales of textures effectively. The development in multi-resolution analysis such as Gabor and wavelet transform help to overcome this difficulty. This paper describes the texture characterization system using (i) Wavelet Statistical Features (WSF) obtained from 3-level Discrete Wavelet Transformed (DWT) images, (ii) Wavelet Co-occurrence Features (WCF) of one level wavelet transformed images in detail.

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