Method of Footprint Image Stitching Based on Multiscale SIFT Feature Matching

2013 ◽  
Vol 303-306 ◽  
pp. 1056-1059
Author(s):  
Sen Wang ◽  
Yin Hui Zhang ◽  
Zhong Hai Shi ◽  
Zi Fen He
Keyword(s):  
Wavelet Transform ◽  
Feature Matching ◽  
Wavelet Coefficient ◽  
Low Frequency ◽  
Original Method ◽  
Inverse Transformation ◽  
Image Stitching ◽  
Image Splicing ◽  
Sift Feature ◽  
Matching Pair

The image stitching method is widely used into the suspect's footprint information extraction. In order to improve the image detail and the matching precision, the Footprint map image stitching method which is based on the wavelet transform and the SIFT feature matching is put forward. The wavelet transform in this method is perform based on the pretreatment of image, move the low frequency wavelet coefficient to zero, adjusting thresholds of the high frequency wavelet coefficient and inverse transformation, then, use the SIFT to extract and match the key-points of the processed images. For the error matching pair of coarse match, you can use the RANSAC to filter them out. This article demonstrates its advantage through to the original image splicing comparisons. The experimental results show that the method display more clear detail and the precision of matching than the original method.

Aeroacoustic analysis of slat tones

2021 ◽  
Vol 263 (1) ◽  
pp. 5650-5663
Author(s):  
Hasan Kamliya Jawahar ◽  
Syamir Alihan Showkat Ali ◽  
Mahdi Azarpeyvand
Keyword(s):  
Wavelet Transform ◽  
Surface Pressure ◽  
Wavelet Coefficient ◽  
Pressure Fluctuations ◽  
Low Frequency ◽  
Stream Velocity ◽  
High Lift ◽  
Unsteady Surface Pressure ◽  
Slat Noise ◽  
Generation Mechanisms

Experimental measurements were carried out to assess the aeroacoustic characteristics of a 30P30N high-lift device, with particular attention to slat tonal noise. Three different types of slat modifications, namely slat cove filler, serrated slat cusp, and slat finlets have been experimentally examined. The results are presented for an angle of attack of α = 18 at a free-stream velocity of U = 30 m/s, which corresponds to a chord-based Reynolds number of Re = 7 x 10. The unsteady surface pressure near the slat region and far-field noise were made simultaneously to gain a deeper understanding of the slat noise generation mechanisms. The nature of the low-frequency broadband hump and the slat tones were investigated using higher-order statistical approaches for the baseline 30P30N and modified slat configurations. Continuous wavelet transform of the unsteady surface pressure fluctuations along with secondary wavelet transform of the broadband hump and tones were carried out to analyze the intermittent events induced by the tone generating resonant mechanisms. Stochastic analysis of the wavelet coefficient modulus of the surface pressure fluctuations was also carried out to demonstrate the inherent differences of different tonal frequencies. An understanding into the nature of the noise generated from the slat will help design the new generation of quite high-lift devices.

Analysis and Simulation of Meteorological Wind Fields Based on Wavelet Transform

2014 ◽  
Vol 490-491 ◽  
pp. 1228-1236 ◽  
Author(s):  
Fo Rong Jin ◽  
Wei Rong Wang
Keyword(s):  
Wavelet Transform ◽  
Wavelet Coefficient ◽  
Low Frequency ◽  
Inertial Subrange ◽  
Target Velocity ◽  
Wind Fields ◽  
Transform Method ◽  
Time Frequency ◽  
Velocity Spectra ◽  
Energy Relations

In this work, we examined the non Gauss distribution characteristic and evolution law of the wavelet coefficient of a gust using wavelet transform; according to the time-frequency characteristic, the wavelet transform coefficients and the energy relations of the target velocity spectra are derived; the wavelet coefficient is generated using the cascade model reflecting the turbulent intermittent; the unsteady gust artificial generation method is established based on inverse wavelet transform; and the arbitrary unsteady fluctuation law can be generated by regulating the coefficient of low frequency. The results show that: the natural gust is in good agreement with Karman wind speed spectrum, meets the turbulence-5 / 3 law in the inertial subrange, and exhibits the nature of intermittence and local self-similarity; the artificial wind sequence based on the inverse wavelet transform method shows similar turbulence statistics with natural gust, with which, the effectiveness of the method is confirmed.

scholarly journals Multi-focus Image Fusion Using an Effective Discrete Wavelet Transform Based Algorithm

2014 ◽  
Vol 14 (2) ◽  
pp. 102-108 ◽  
Author(s):  
Yong Yang ◽  
Shuying Huang ◽  
Junfeng Gao ◽  
Zhongsheng Qian
Keyword(s):  
Wavelet Transform ◽  
Image Fusion ◽  
Discrete Wavelet Transform ◽  
High Frequency ◽  
Low Frequency ◽  
Objective Evaluation ◽  
Discrete Wavelet ◽  
Evaluation Indexes ◽  
Fused Image ◽  
Focus Image

Abstract In this paper, by considering the main objective of multi-focus image fusion and the physical meaning of wavelet coefficients, a discrete wavelet transform (DWT) based fusion technique with a novel coefficients selection algorithm is presented. After the source images are decomposed by DWT, two different window-based fusion rules are separately employed to combine the low frequency and high frequency coefficients. In the method, the coefficients in the low frequency domain with maximum sharpness focus measure are selected as coefficients of the fused image, and a maximum neighboring energy based fusion scheme is proposed to select high frequency sub-bands coefficients. In order to guarantee the homogeneity of the resultant fused image, a consistency verification procedure is applied to the combined coefficients. The performance assessment of the proposed method was conducted in both synthetic and real multi-focus images. Experimental results demonstrate that the proposed method can achieve better visual quality and objective evaluation indexes than several existing fusion methods, thus being an effective multi-focus image fusion method.

Trial Study on Methods of Damage Extent Identification Based on Wavelet Transform of Strain Signal

2010 ◽  
Vol 163-167 ◽  
pp. 2543-2548
Author(s):  
Jin Fan ◽  
Hong Po Liu
Keyword(s):  
Wavelet Transform ◽  
Wavelet Coefficient ◽  
Maximum Modulus ◽  
Steel Beam ◽  
Simply Supported ◽  
Relative Damage ◽  
Damage Extent ◽  
Strain Signal

Wavelet transform of strain signal can be used in the damage relative damage extent identification. The proposed method is validated by trial on a simply supported steel beam. And meanwhile the relative damage extent can be identified by drawing the curve of the maximum modulus of the wavelet coefficient and damage extent.

A low complexity image stitching using advanced feature matching in mobile environments

2014 ◽  
Vol 10 (2) ◽  
pp. 129-136 ◽  
Author(s):  
Hyochang Ahn ◽  
Yong-Hwan Lee ◽  
June-Hwan Lee ◽  
Han-Jin Cho
Keyword(s):  
Feature Matching ◽  
Low Complexity ◽  
Image Stitching ◽  
Mobile Environments

scholarly journals An Image Denoising Method with Enhancement of the Directional Features Based on Wavelet and SVD Transforms

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Min Wang ◽  
Zhen Li ◽  
Xiangjun Duan ◽  
Wei Li
Keyword(s):  
Wavelet Transform ◽  
Singular Value Decomposition ◽  
Image Denoising ◽  
High Frequency ◽  
Low Frequency ◽  
Singular Value ◽  
Denoising Method ◽  
Diagonal Part ◽  
Value Decomposition ◽  
Image Part

This paper proposes an image denoising method, using the wavelet transform and the singular value decomposition (SVD), with the enhancement of the directional features. First, use the single-level discrete 2D wavelet transform to decompose the noised image into the low-frequency image part and the high-frequency parts (the horizontal, vertical, and diagonal parts), with the edge extracted and retained to avoid edge loss. Then, use the SVD to filter the noise of the high-frequency parts with image rotations and the enhancement of the directional features: to filter the diagonal part, one needs first to rotate it 45 degrees and rotate it back after filtering. Finally, reconstruct the image from the low-frequency part and the filtered high-frequency parts by the inverse wavelet transform to get the final denoising image. Experiments show the effectiveness of this method, compared with relevant methods.

A Feature Extracting Method for Chinese Character Recognition of License Plate Based on Elastic Mesh and Wavelet Transform

2013 ◽  
Vol 760-762 ◽  
pp. 1452-1456
Author(s):  
Chao Zheng ◽  
Hua Yang ◽  
Xing Yang ◽  
Chao Chao Huang ◽  
Xiao Di Wu
Keyword(s):  
Wavelet Transform ◽  
Character Recognition ◽  
Chinese Character ◽  
Wavelet Coefficient ◽  
Difficult Problem ◽  
License Plate ◽  
Structure Information ◽  
Feature Extracting ◽  
Chinese Character Recognition ◽  
Character Feature

Low-resolution Chinese character recognition of license plate is always a difficult problem. For solving it, we must think about the distinctiveness of character feature and the counting speed of method simultaneously. In this paper, we proposed a simple and effective feature extraction algorithm. First, extract the statistical feature of Chinese character based on decomposing stroke with wavelet transform. Second, apply Elastic Mesh Algorithm into extracting wavelet coefficient of decomposing stroke to get the structure information of Chinese character. The experimental results show the method is robust against low quality Chinese characters, such as skew, fuzzy, glue, distorted character, and easy to be used in actual projects with simple advantage.

Medical Image Feature Matching Based on Wavelet Transform and SIFT Algorithm

2011 ◽  
Vol 65 ◽  
pp. 497-502
Author(s):  
Yan Wei Wang ◽  
Hui Li Yu
Keyword(s):  
Wavelet Transform ◽  
Wavelet Transforms ◽  
Medical Image ◽  
Feature Matching ◽  
Image Feature ◽  
Scale Invariant ◽  
Sift Algorithm ◽  
Matching Algorithm ◽  
Invariant Feature ◽  
Scale Invariant Feature

A feature matching algorithm based on wavelet transform and SIFT is proposed in this paper, Firstly, Biorthogonal wavelet transforms algorithm is used for medical image to delaminating, and restoration the processed image. Then the SIFT (Scale Invariant Feature Transform) applied in this paper to abstracting key point. Experimental results show that our algorithm compares favorably in high-compressive ratio, the rapid matching speed and low storage of the image, especially for the tilt and rotation conditions.

Digital Watermarking for 3D Polygonal Model Based on Wavelet Transform

1999 ◽  
Author(s):  
Hiroaki Date ◽  
Satoshi Kanai ◽  
Takeshi Kishinami
Keyword(s):  
Wavelet Transform ◽  
Digital Watermarking ◽  
Copyright Protection ◽  
Affine Transformation ◽  
Wavelet Coefficient ◽  
Original Data ◽  
Geometric Error ◽  
Digital Data ◽  
Cad Cam ◽  
Polygonal Model

Abstract Recently, much interest is being taken in a method to protect the copyright of digital data and prevent illegal duplication of it. However, in the area of CAD/CAM and CG, there are no effective ways to protect the copyright of the 3D geometric models. As a first step to solve this problem, a new digital watermarking method for 3D polygonal models is introduced in this paper. Watermarking is one of the copyright protection methods where an invisible watermark is secretly embedded into the original data. The proposed watermarking method is based on the wavelet transform (WT) and multi-resolution representation (MRR) of the polygonal model. The watermark can be embedded in the large wavelet coefficient vectors at various resolution levels of the MRR. This makes the embedded watermark imperceptible and invariant to the affine transformation, and also makes the control of the geometric error caused by the watermarking reliable.

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