2018
DOI: 10.1016/j.infrared.2018.08.004
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Infrared and visible image fusion using co-occurrence filter

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Cited by 35 publications
(15 citation statements)
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“…The techniques are ordered according to time, chronologically from the oldest to the newest algorithm. The fusion process is carried out according to techniques described in [5, 8, 9, 27, 31, 32, 34, 35, 38–43]. The dataset used is the most challenging dataset.…”
Section: Experiments and Resultsmentioning
confidence: 99%
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“…The techniques are ordered according to time, chronologically from the oldest to the newest algorithm. The fusion process is carried out according to techniques described in [5, 8, 9, 27, 31, 32, 34, 35, 38–43]. The dataset used is the most challenging dataset.…”
Section: Experiments and Resultsmentioning
confidence: 99%
“…So, these parameters are exploited to influence the smoothing algorithm such that the effective edges remain preserved. Mathematically, it can be defined as [38] right left right left right left right left right left right left0.278em 2em 0.278em 2em 0.278em 2em 0.278em 2em 0.278em 2em 0.278em3ptIm=nϵN(m)wfalse(m,nfalse)InnϵN(m)wfalse(m,nfalse)where Im and In are the output and input pixel values, respectively. The Gaussian filter kernel and bilateral filter kernel are defined in Section 2.4 and if we replace the Gaussian kernel with the normalised co‐occurrence matrix [38] right left right left right left right left right left right left0.278em 2em 0.278em 2em 0.278em 2em 0.278em 2em 0.278em 2em 0.278em3ptMi,j=bold-italicCfalse(i,jfalse)/h)(ihfalse(jfalse)where bold-italicCfalse(i,jfalse) is the co‐occurrence matrix, hfalse(ifalse) and hfalse(jfalse) are the frequencies of occurrence of pixels i and j , then co‐occurrence filter is obtained.…”
Section: State‐of‐the‐artmentioning
confidence: 99%
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“…e fusion methods used for experiment in this paper are as follows: guided filter algorithm (GFF) [23], two-scale using saliency detection (TSD) [37], contrast pyramid algorithm (CP) [40], convolution sparse representation (CSR) algorithm [41], gradient-based transfer and total variation algorithm (GTTV) [42], weighted least squares optimization (WLS) algorithm [22], multiple visual feature measurement-based fusion (MVFMF) approach [24], co-occurrence filter-based fusion method (CoF) [25], cross bilateral filter (CBF) [21], targetenhanced multiscale transform decomposition algorithm (TEMTD) [17], and latent low-rank representation algorithm (LLRR) [43].…”
Section: Compared Methodsmentioning
confidence: 99%
“…Bilateral filter [20], cross bilateral filter [21], iterative guided filtering [22], guided filtering (GFF) [23], gradient domain-guided filtering (GDGF) [24], and co-occurrence filter [25] (CoF) methods are the popular local filter-based methods. e visual quality of the fused images could be significantly enhanced through the mentioned filtering methods.…”
Section: Introductionmentioning
confidence: 99%