A De-Noising Algorithm Dealing with Spectral Signal in Color Measurement Based on Wavelet Transform

2013 ◽  
Vol 303-306 ◽  
pp. 1043-1047
Author(s):  
Hai Long Li ◽  
Jun Xu ◽  
Wen Jia ◽  
Sheng Zhu ◽  
Sha Li ◽  
...  
Keyword(s):  
Wavelet Transform ◽  
Spectral Data ◽  
Traditional Method ◽  
Spectral Measurement ◽  
Common Method ◽  
Color Measurement ◽  
Spectral Signal

Spectral measurement is a common method for color measurement. Spectral data of color samples gathered by spectrometers contains a series of noises. The traditional de-noising methods have their limitation in dealing with such signal. In this paper, a de-noising method is proposed for spectral signal based on Wavelet Transform. Compared the performance of our de-nosing method with the traditional method, the results show that our method a better effect.

scholarly journals The NMR Spectral Measurement Database: A System for Organizing and Accessing NMR Spectra of Therapeutic Proteins

2021 ◽  
Vol 126 ◽  
Author(s):  
Niksa Blonder ◽  
Frank Delaglio
Keyword(s):  
Nuclear Magnetic Resonance ◽  
Magnetic Resonance ◽  
Spectral Data ◽  
Data Storage ◽  
Nmr Spectra ◽  
Therapeutic Proteins ◽  
Data Access ◽  
Protein Therapeutics ◽  
Spectral Measurement ◽  
Storage And Retrieval

The Nuclear Magnetic Resonance Spectral Measurement Database (NMR-SMDB) was developed for the purpose of organizing and searching NMR spectral data of protein therapeutics, linking spectra to corresponding sample information and enabling quick access to full datasets and entire studies. In addition to supporting internal research at the National Institute of Standards and Technology (NIST), the system could facilitate data access to stakeholders outside of NIST, and future versions of the database software itself could be installed by others for their own data storage and retrieval.

Spectral feature extraction based on continuous wavelet transform and image segmentation for peak detection

2020 ◽  
Vol 12 (2) ◽  
pp. 169-178 ◽  
Author(s):  
Guofeng Yang ◽  
Jiacai Dai ◽  
Xiangjun Liu ◽  
Meng Chen ◽  
Xiaolong Wu
Keyword(s):  
Feature Extraction ◽  
Image Segmentation ◽  
Wavelet Transform ◽  
Continuous Wavelet Transform ◽  
Spectral Feature ◽  
Peak Detection ◽  
Continuous Wavelet ◽  
Crucial Step ◽  
Spectral Signal

Peak detection is a crucial step in spectral signal pre-processing.

An Analysis of Deviations of Cylindrical Surfaces with the Use of Wavelet Transform

2013 ◽  
Vol 20 (1) ◽  
pp. 139-150 ◽  
Author(s):  
Krzysztof Stępień ◽  
Włodzimierz Makieła
Keyword(s):  
Wavelet Transform ◽  
Fourier Analysis ◽  
Mechanical Engineering ◽  
Science And Technology ◽  
Measurement Data ◽  
Common Method ◽  
Good Tool ◽  
Signal Measurement ◽  
Stationary Signals ◽  
Analyze Data

Abstract Wavelet transform becomes a more and more common method of processing 3D signals. It is widely used to analyze data in various branches of science and technology (medicine, seismology, engineering, etc.). In the field of mechanical engineering wavelet transform is usually used to investigate surface micro- and nanotopography. Wavelet transform is commonly regarded as a very good tool to analyze non-stationary signals. However, to analyze periodical signals, most researchers prefer to use well-known methods such as Fourier analysis. In this paper authors make an attempt to prove that wavelet transform can be a useful method to analyze 3D signals that are approximately periodical. As an example of such signal, measurement data of cylindrical workpieces are investigated. The calculations were performed in the MATLAB environment using the Wavelet Toolbox.

A VLSI Architecture of 2-D Discrete Wavelet Transform for Reducing Computation Time

2013 ◽  
Vol 284-287 ◽  
pp. 2463-2467
Author(s):  
Chin Fa Hsieh ◽  
Tsung Han Tsai ◽  
Cheng Chung Liu
Keyword(s):  
Wavelet Transform ◽  
Discrete Wavelet Transform ◽  
Traditional Method ◽  
Computing Time ◽  
Vlsi Architecture ◽  
Computation Time ◽  
Original Data ◽  
Discrete Wavelet ◽  
Two Dimensional

In this paper, we propose an efficient VLSI architecture for implementing the forward two-dimensional discrete wavelet transform (2D DWT), which is computed without utilizing the traditional method of rows-by-columns or columns-by-rows. On account of the relation form within the original data, we apply masks of different window sizes to the transform and design the architecture based on these different window masks. On the comparison of the computing time, the proposed architecture requires only N*N/4 clock cycles for an N*N image, while it takes N*N clock cycles for the traditional row-by-column/column-by-row 2D DWT. The proposed architecture has a better performance than other designs reported in the literature.

An intensity correction method combined with plasma position information for laser-induced breakdown spectroscopy

2017 ◽  
Vol 32 (12) ◽  
pp. 2371-2377 ◽  
Author(s):  
P. Zhang ◽  
L. X. Sun ◽  
H. B. Yu ◽  
P. Zeng ◽  
L. F. Qi ◽  
...  
Keyword(s):  
Spectral Data ◽  
Imaging System ◽  
Positional Information ◽  
Correction Method ◽  
Laser Induced Breakdown Spectroscopy ◽  
Position Information ◽  
Breakdown Spectroscopy ◽  
Plasma Position ◽  
Spectral Signal ◽  
Laser Induced Breakdown

The uncertainty of the spectral data is one of the most important issues for LIBS. To reduce the uncertainty, an imaging system was deployed and a model was built based on both the spectral signal and the positional information in this work.

A Recognition Method of Gait by Wavelet Transform and Genetic Algorithm

2014 ◽  
Vol 701-702 ◽  
pp. 274-278 ◽  
Author(s):  
Yun Shi ◽  
Xu Qi Wang ◽  
Yu Cheng Zhang
Keyword(s):  
Genetic Algorithm ◽  
Wavelet Transform ◽  
Real Time ◽  
Traditional Method ◽  
Feature Vector ◽  
Gait Recognition ◽  
Recognition Method ◽  
Recognition Model ◽  
Method Of Correlation ◽  
Correlation Matching

A new recognition method of gait is presented in this paper. In this method, the feature vector of gait is found by multidistinguish analysis of wavelet transform, and gait is recognized by genetic algorithm (GA). This method is different from the traditional method of correlation matching recognition gait. First, the stored space reduces greatly because recognition model is used to replace the store of gait profile image template. Thus this method reduces stored memory greatly. Second real-time is ensured in the process of gait recognition by using GA. The experiments of recognition using the three kinds of gait databases are performed. The experiment results show the feasibility and effectiveness of the proposed method.

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