On the measurement of a multidimensional concept of structural similarity

Crespo, Nuno; Simões, Nádia

doi:10.1016/j.econlet.2012.01.024

Cited by 9 publications

(13 citation statements)

References 5 publications

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“…The first experiment is conducted to evaluate the visual quality of the reconstruction. We adopt the popular structural similarity index (SSIM) Crespo and Simoes (2012) to objectively assess the perceptual quality. The structural similarity is highest when the SSIM value is equal to one.…”

Section: Experimental Results and Analysismentioning

confidence: 99%

Color monogenic wavelet transform for multichannel image denoising

Gai

Zhang

Yang

et al. 2016

Multidim Syst Sign Process

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This paper proposes an effective color image denoising algorithm using the combination color monogenic wavelet transform (CMWT) with a trivariate shrinkage filter. The CMWT coefficients are one order of magnitude with three phases: two phases encode the local color information while the third contains geometric information relating to texture within the color image. In the CMWT domain, a trivariate Gaussian distribution is applied to capture statistical dependencies between the CMWT coefficients, and then a trivariate shrinkage filter is derived using a maximum a posteriori estimator. The performance of the proposed algorithm is experimentally verified using a variety of color test images with a range of noise levels in terms of PSNR and visual quality. The experimental results demonstrate that the proposed algorithm is equal to or better than current state-of-the-art algorithms in both visual and quantitative performance.

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Section: Experimental Results and Analysismentioning

confidence: 99%

Color monogenic wavelet transform for multichannel image denoising

Gai

Zhang

Yang

et al. 2016

Multidim Syst Sign Process

View full text Add to dashboard Cite

show abstract

“…Recently, Crespo and Simões (2012) propose two extensions to this standard measure, incorporating Finally, the average of these values-which will be used below for the construction of our GSS measures-is given by:…”

Section: Methodsmentioning

confidence: 99%

“…Our starting point is a modified (and richer) version of the Krugman index that not only incorporates the extensions suggested for trade analysis by Crespo and Simões (2012), but also allows us to address the several specificities of measuring geographical structural similarity in tourism flows. The most important of these specificities is related to a particular but crucial issue: when we compare the export or import composition of two countries we know that the range of products they can potentially trade is exactly the same.…”

Section: A Standard Measure Of Structural Similaritymentioning

confidence: 99%

Competition in Tourism Arrivals: A Multidimensional Index of Geographical Structural Similarity

2016

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Given the economic importance of the tourism sector, countries actively compete for attracting tourism flows. In a bilateral perspective, an important determinant of the degree of competition is the geographical structure of tourism inflows (i.e., the relative importance of the different source countries). A higher overlap of these flows indicates greater competition. The present study proposes a methodological approach to quantify this overlap. Taking some indicators traditionally used in international trade analysis as inspiration, we propose a methodology that measures, for each pair of countries, the degree of similarity between the geographical structures of tourism inflows. The methodology takes a multidimensional concept of structural similarity in order to incorporate relevant dimensions of international tourism flows today.

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“…The traditional approach to measure structural similarity (i.e., KSI or its adaptations) does not consider the degree of dissimilarity between sectors. With the aim of adjusting E ihm in order to capture this dimension, we propose a generalised version of the procedure suggested by Crespo and Simões (). To that end, making use of the different levels of sectoral disaggregation that comprise a specific statistical nomenclature, we calculate the weighted average of the structural similarity indexes obtained at different levels of sectoral disaggregation ( g = 1, 2, …, G ; in which G is the most disaggregated level), with the weight of each level given by α g :

S_{i h m} = {false\sum}_{g = 1}^{G} {normalα}^{g} E_{i h m}^{g},

with

\sum_{g = 1}^{G} {normalα}^{g} = 1

.…”

Section: Methodsmentioning

confidence: 99%

“…Crespo and Simões () propose an even larger measure of structural similarity, which besides sectoral shares similarity and intra‐sectoral similarity also incorporates inter‐sectoral similarity (evaluating how different the distinct sectors are). The basic argument is that sectors have distinct levels of dissimilarity among them in what concerns their production requirements.…”

Section: Introductionmentioning

confidence: 99%

A contribution to a multidimensional analysis of trade competition

2017

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International trade grew substantially throughout the last decades and international relations became more important for the economic performance of the countries. Simultaneously, new poles emerged in the international arena leading to growing competition for higher market shares. Therefore, trade competition is a critical dimension of analysis for applied international trade studies. We propose a conceptual framework for measuring this phenomenon by combining some critical previous contributions to build a multidimensional and more comprehensive concept, which defines trade competition as a function of the degree of both structural similarity and total exports overlap. Moreover, structural similarity should take into account three elements: sectoral shares similarity, inter‐sectoral similarity (evaluating how different the distinct sectors are) and intra‐sectoral similarity (proximity in terms of quality ranges exported). Several measures are proposed to empirically capture the concept suggested. Finally, we present an example including the exports of six European economies (Germany, France, the United Kingdom, Greece, Hungary and Sweden) to 124 destination markets (in 2007, 2011, 2015) in order to illustrate the application of the concept and measures suggested.

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On the measurement of a multidimensional concept of structural similarity

Cited by 9 publications

References 5 publications

Color monogenic wavelet transform for multichannel image denoising

Color monogenic wavelet transform for multichannel image denoising

Competition in Tourism Arrivals: A Multidimensional Index of Geographical Structural Similarity

A contribution to a multidimensional analysis of trade competition

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