Vector Map Data Compression with Wavelets

2000 ◽  
Vol 53 (3) ◽  
pp. 437-449 ◽  
Author(s):  
Juliette W. Ioup ◽  
Marlin L. Gendron ◽  
Maura C. Lohrenz
Keyword(s):  
Data Compression ◽  
Wavelet Transforms ◽  
Wavelet Packet ◽  
Naval Research ◽  
Data Sets ◽  
Commanding Officer ◽  
Vector Map ◽  
Error Measures ◽  
Map Data ◽  
Mean Square Errors

This paper was first presented at a Symposium on ‘Advanced Moving-Map Displays’ held on the 3rd and 4th of August 1999 by the US Naval Research Laboratory Detachment at the NASA Stennis Space Centre, Mississippi, and is reproduced in modified form with the kind permission of the NRL Commanding Officer, Captain Douglas H. Rau USN.Wavelets and wavelet transforms can be used for vector-map data compression. The choice of wavelet, the level of decomposition, the method of thresholding, the height of the threshold, relative CPU times and file sizes, and reconstructed map appearance were investigated using the Wavelet Toolbox of MATLAB. Quantitative error measures were obtained. For two test vector-map data sets consisting of longitude and latitude points, compressions of 35 to 50 percent (1·5[ratio ]1 to 2[ratio ]1) were obtained with root-mean-square errors less than 0·003 to 0·01° longitude/latitude for wavelet packet decompositions using selected wavelets.

Vector Map Data Compression Using Polyline Feature

2014 ◽  
Vol E97.A (7) ◽  
pp. 1595-1604
Author(s):  
Suk-Hwan LEE ◽  
Won-Joo HWANG ◽  
Jai-Jin JUNG ◽  
Ki-Ryong KWON
Keyword(s):  
Data Compression ◽  
Vector Map ◽  
Map Data

scholarly journals Hybrid Polyline Simplification for GIS Vector Map Data Compression

2013 ◽  
Vol 16 (4) ◽  
pp. 418-429 ◽  
Author(s):  
Dae-Yeop Im ◽  
Bong-Joo Jang ◽  
Suk-Hwan Lee ◽  
Seong-Geun Kwon ◽  
Ki-Ryong Kwon
Keyword(s):  
Data Compression ◽  
Vector Map ◽  
Map Data

Human Factors in Vector Map Design: The Importance of Task-Display Dependence

2000 ◽  
Vol 53 (1) ◽  
pp. 54-67 ◽  
Author(s):  
Christopher D. Wickens
Keyword(s):  
Human Factors ◽  
Computational Models ◽  
Three Dimensional ◽  
Naval Research ◽  
Commanding Officer ◽  
Digital Maps ◽  
Vector Map ◽  
Map Design ◽  
The Many ◽  
The One

This paper, and the following 5 papers, were first presented at a Symposium on ‘Advanced Moving-Map Displays’ held on the 3rd and 4th of August 1999 at the US Naval Research Laboratory Detachment at the NASA Stennis Space Centre, Mississippi and are reproduced in modified form with the kind permission of the NRL Commanding Officer, Captain Douglas H. Rau USN.The role of human factors in map design is to serve as a mediator between the technology availed by electronic digital maps (particularly vector maps) on the one hand, and the many tasks performed by the user on the other. Simply put, no one map is best suited for all tasks. The appropriate mapping of map to task is, in turn, mediated by a series of information processing principles, articulated by the engineering psychologist. The field is on the threshold of being able to provide computational models, based on these principles, that will provide guidance to the map designer as to the circumstances that make one map format better than another for a particular application. This paper describes these principles as applied to two domains of vector map design: the domain of three-dimensional maps, and the domain of database overlay.

scholarly journals Vector Map Data compression based on Douglas Peucker Simplification Algorithm and Bin Classification

2015 ◽  
Vol 18 (3) ◽  
pp. 298-311 ◽  
Author(s):  
Jin-Hyeok Park ◽  
Bong Joo Jang ◽  
Oh Jun Kwon ◽  
Jae-Jin Jeong ◽  
Suk-Hwan Lee ◽  
...  
Keyword(s):  
Data Compression ◽  
Vector Map ◽  
Map Data

A New Method for Characterizing Replacement Rate Variation in Molecular Sequences: Application of the Fourier and Wavelet Models to Drosophila and Mammalian Proteins

Genetics ◽  
2000 ◽  
Vol 154 (1) ◽  
pp. 381-395
Author(s):  
Pavel Morozov ◽  
Tatyana Sitnikova ◽  
Gary Churchill ◽  
Francisco José Ayala ◽  
Andrey Rzhetsky
Keyword(s):  
Wavelet Transforms ◽  
Parametric Bootstrap ◽  
Real Data ◽  
New Method ◽  
Rate Variation ◽  
Discrete Wavelet ◽  
Data Sets ◽  
Ratio Test ◽  
Replacement Rate ◽  
New Models

Abstract We propose models for describing replacement rate variation in genes and proteins, in which the profile of relative replacement rates along the length of a given sequence is defined as a function of the site number. We consider here two types of functions, one derived from the cosine Fourier series, and the other from discrete wavelet transforms. The number of parameters used for characterizing the substitution rates along the sequences can be flexibly changed and in their most parameter-rich versions, both Fourier and wavelet models become equivalent to the unrestricted-rates model, in which each site of a sequence alignment evolves at a unique rate. When applied to a few real data sets, the new models appeared to fit data better than the discrete gamma model when compared with the Akaike information criterion and the likelihood-ratio test, although the parametric bootstrap version of the Cox test performed for one of the data sets indicated that the difference in likelihoods between the two models is not significant. The new models are applicable to testing biological hypotheses such as the statistical identity of rate variation profiles among homologous protein families. These models are also useful for determining regions in genes and proteins that evolve significantly faster or slower than the sequence average. We illustrate the application of the new method by analyzing human immunoglobulin and Drosophilid alcohol dehydrogenase sequences.

The use of wavelet transforms for improved interpretation of airborne transient electromagnetic data

Geophysics ◽  
2013 ◽  
Vol 78 (3) ◽  
pp. E117-E123 ◽  
Author(s):  
Vanessa Nenna ◽  
Adam Pidlisecky
Keyword(s):  
Wavelet Transforms ◽  
Oil And Gas ◽  
Spatial Scales ◽  
Data Sets ◽  
Data Set ◽  
Topographic Features ◽  
Transient Electromagnetic ◽  
Power Maps ◽  
Southern Alberta ◽  
Cultural Noise

The continuous wavelet transform (CWT) is used to create maps of dominant spatial scales in airborne transient electromagnetic (ATEM) data sets to identify cultural noise and topographic features. The introduced approach is applied directly to ATEM data, and does not require the measurements be inverted, though it can easily be applied to an inverted model. For this survey, we apply the CWT spatially to B-field and dB/dt ATEM data collected in the Edmonton-Calgary Corridor of southern Alberta. The average wavelet power is binned over four ranges of spatial scale and converted to 2D maps of normalized power within each bin. The analysis of approximately 2 million soundings that make up the survey can be run on the order of minutes on a 2.4 GHz Intel processor. We perform the same CWT analysis on maps of surface and bedrock topography and also compare ATEM results to maps of infrastructure in the region. We find that linear features identified on power maps that differ significantly between B-field and dB/dt data are well correlated with a high density of infrastructure. Features that are well correlated with topography tend to be consistent in power maps for both types of data. For this data set, use of the CWT reveals that topographic features and cultural noise from high-pressure oil and gas pipelines affect a significant portion of the survey region. The identification of cultural noise and surface features in the raw ATEM data through CWT analysis provides a means of focusing and speeding processing prior to inversion, though the magnitude of this affect on ATEM signals is not assessed.

Medical Image Compression Using Integer Wavelet Transformations

2011 ◽  
pp. 277-286
Author(s):  
B. Ramakrishnan ◽  
N. Sriraam
Keyword(s):  
Wavelet Transform ◽  
Wavelet Transforms ◽  
Medical Images ◽  
Lossy Compression ◽  
Data Sets ◽  
Optimal Method ◽  
Medical Image Compression ◽  
Integer Wavelet ◽  
Wavelet Transformations ◽  
Lossless And Lossy Compression

In this chapter, we have focused on compression of medical images using integer wavelet transforms. Lifting transforms such as S, TS, S+P(B), S+P(C), 5/3, 2+@, 2, 9/7-M and 9/7-F transforms are used to evaluate the performances of lossless and lossy compression. Four medical images, namely, MRI, CT, ultrasound, and angiograms are used as test data sets. It is found from the experiments that, among the different transforms, the 9/7-M wavelet transform is identified as the optimal method for lossless and lossy compression of medical images.

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