Infrared and visible image fusion based on intuitionistic fuzzy sets

Zhang, Kang; Huang, Yongdong; Yuan, Xia; Ma, Haoyan; Zhao, Chenglin

doi:10.1016/j.infrared.2019.103124

Cited by 25 publications

(12 citation statements)

References 28 publications

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“…Building on IFS, many MCDM methods have been proposed one after another, such as a novel EDAS approach for assessment of healthcare waste disposal technology [28], a new approach to multi-criteria decision-making [29] and the ELECTRE multi-criteria analysis approach for ranking alternatives [30]. Alternatively, IFS has found an increasingly wide utilization in a wide range of fields, such as image fusion [31], pattern recognition [32] and energy evaluation [33]. Moreover, considering that a single membership degree may not express the decision information well in some situations.…”

Section: Fuzzy Sets and Fuzzy Preference Relationsmentioning

confidence: 99%

Ranking Tourist Attractions through Online Reviews: A Novel Method with Intuitionistic and Hesitant Fuzzy Information Based on Sentiment Analysis

Qin

Wang

Zhang

2021

Int. J. Fuzzy Syst.

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Online tourist reviews are the real feeling of tourists after the journey, which have a strong reference value for potential tourists to make travel decisions. However, it is almost impossible for a potential tourist to look through the massive online reviews related to tourist attractions (TAs) so that he/she can make the most appropriate decision. To this end, this paper proposes a recommender system to rank the alternative TAs through online reviews based on aspect-level sentiment analysis and multi-criteria decision-making (MCDM) with intuitionistic and hesitant fuzzy information. In this methodology, the aspects that the experienced tourists concern are extracted from online reviews to construct a three-level evaluation system (including target layer, criteria layer and sub-criteria layer), which not only ensures the comprehensive evaluation of TAs as much as possible, but also reduces the complexity of the decision-making process. Then, the online reviews related to these sub-criteria are transformed into the corresponding intuitionistic and hesitant fuzzy performance scores through aspect-level sentiment analysis. Furthermore, in order to obtain the final ranking result that more in line with the expectations of the potential tourist, the preference information from the potential tourist and experienced tourists is integrated to determine the weights of criteria. Subsequently, the intuitionistic and hesitant fuzzy TOPSIS (IHF-TOPSIS) method is proposed to rank the alternative TAs. Finally, a case study is provided to verify the validity and applicability of the methodology.

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Section: Fuzzy Sets and Fuzzy Preference Relationsmentioning

confidence: 99%

Ranking Tourist Attractions through Online Reviews: A Novel Method with Intuitionistic and Hesitant Fuzzy Information Based on Sentiment Analysis

Qin

Wang

Zhang

2021

Int. J. Fuzzy Syst.

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“…(2) Entropy (EN) [51]: Entropy is used in information theory to measure how much information contained and we can define it as: where p(i) is the gray frequency of a result image, and L is the gray level of the result image.…”

Section: B Objective Evaluationmentioning

confidence: 99%

From Coarse to Fine (FC2F): A New Scheme of Colorizing Thermal Infrared Images

et al. 2020

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Colorization of the thermal infrared image is an unsolved problem because usually there is no one-to-one relationship between an object's color and its temperature. In this paper, we propose a new colorization scheme to address this problem. We first create a coarse colorization image that maintains cross-correlation between its RGB channels. Then the matrix of shift, rotation, and scaling between the coarse colorization image and a source natural color image is constructed. Finally, the transformations act on the coarse colorization image to obtain the resultant image, which has the appearance of the source image. Experiments demonstrate the effectiveness of the new scheme and show its superiority to other state-of-theart methods. The new scheme can be easily extended to the colorization of low illumination images and near-infrared images.

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“…A novel image fusion algorithm, which based on two-scale image decomposition integrated with fuzzy set theory and image morphology, was introduced by Zhang et al [49]. They presented a new fusion method based on non-subsampled contourlet transform (NSCT) with intuitionistic fuzzy sets for the infrared and visible image fusion [50]. Yang et al proposed a novel multimodal sensor medical image fusion method based on type-2 fuzzy logic in NSCT domain [51].…”

Section: Introductionmentioning

confidence: 99%