A fast intensity-hue-saturation fusion technique with spectral adjustment for IKONOS imagery

By T. Tu, P. Huang, Chung-Ling Hung, Chien-Ping Chang. IEEE Geoscience and Remote Sensing Letters, 2004

644 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition, Media Technology

View Paper: https://www.semanticscholar.org/paper/e6ffbdfd39d72ac9933b4c942a4888bb80412457

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In Computer Vision and Pattern Recognition

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Citations in the corpus

Multi-source remote sensing data fusion: status and trends (2010, methodology): “The original algorithm is suitable for exactly three MS band fusion but has been generalised (GIHS) to support fusion of near-infrared (NIR) images (Tu et al. 2004).”
A review of remote sensing image fusion methods (2016, methodology): “Intensity-Hue-Saturation (IHS) [39], principal component analysis (PCA) [9], Brovey transform (BT) [40], and Gram-Schmidt (GS) [41] belong to this class of pansharpening.”
Synthesis of Multispectral Images to High Spatial Resolution: A Critical Review of Fusion Methods Based on Remote Sensing Physics (2008, background): “Tu et al. [14], [ 15 ] pioneered a new way of tackling the linear”
Hyperspectral Pansharpening: A Review (2015, background): “where the weights w , , , , w w w i m T 1 f f = m 6 @ measure the spectral overlap among the spectral bands and the PAN image [6], [40].”
Contrast and Error-Based Fusion Schemes for Multispectral Image Pansharpening (2014, methodology): “Furthermore, the FIHS method employs (10) for the injection of details [12].”
A New Pan-Sharpening Method Using a Compressed Sensing Technique (2011, methodology): “The proposed method is compared with six commonly used pan-sharpening methods, namely, the generalized IHS (GIHS) [9], the GS transform [11], SVT [16], the ATWT-based method with the CBD injection model [19], the ATWT-based method with the AWLP model [17], and the ATWT-based method with the genetic ”
Target-Adaptive CNN-Based Pansharpening (2017, methodology): “This same approach has been generalized in [3] [Generalized Intensity-Hue-Saturation (GIHS)] to include additional bands.”
Rethinking the Image Fusion: A Fast Unified Image Fusion Network based on Proportional Maintenance of Gradient and Intensity (2020, methodology): “We compare our method with classical meth-ods PCA (Chavez et al. 1991), FISH (Tu et al. 2004) and Brovey (Gillespie, Kahle, and Walker 1986).”
Pixel-level image fusion: A survey of the state of the art (2017, methodology): “2) Methods performed in other transform domains Besides the fusion methods based on muli-scale decomposition or sparse representation, color space 260 and dimension reduction based transforms also have been successfully applied for image fusion, such as the intensity-hue-saturation (IHS) transform [”
Remote Sensing Image Fusion via Sparse Representations Over Learned Dictionaries (2013, methodology): “The proposed method is compared with six popular methods: the Gram–Schmidt (GS) algorithm [30], the fast IHS (FIHS) [3], the SVT [11], the ATWT-based method with the CBD injection model [10], the AWLP [9], and the CS-based method [16].”
Improving Component Substitution Pansharpening Through Multivariate Regression of MS $+$Pan Data (2007, methodology): “In particular, two CS fusion methods, namely, the fast GIHS with spectral adjustment [9] and the GS spectral sharpening of ENVI, are considered.”
A comparative analysis of image fusion methods (2012, positive): “Bu tür uydu görüntülerinde zenginleştirme yapılması için TeMing Tu ve arkadaşlarının 2001 yılında yayınladıkları makalede genelleştirilmiş IHS (GIHS) yöntemi önerilmiştir[7].”
A Convex Formulation for Hyperspectral Image Superresolution via Subspace-Based Regularization (2014, methodology): “Panchromatic images (PANs) typically have a spatial resolution that is even higher than the one of MSIs.”
A New Benchmark Based on Recent Advances in Multispectral Pansharpening: Revisiting Pansharpening With Classical and Emerging Pansharpening Methods (2021, background): “in which the weight vector [ , , , , ] w w w w i N 1 f f = is the first row of the forward transformation matrix [112], [124].”
A survey of classical methods and new trends in pansharpening of multispectral images (2011, methodology): “In order to minimize the spectral distortion in IHS pansharpening, Tu et al.[56] proposed a new adaptive IHS method in which the intensity band approximates the PAN image for IKONOS images as closely as possible.”
A Multiscale and Multidepth Convolutional Neural Network for Remote Sensing Imagery Pan-Sharpening (2017, methodology): “Examples of CS-based methods are the typical intensity-hue-saturation fusion methods [1], [2], the principal component analysis fusion method [3], the Gram–Schmidt (GS) fusion method [4], and adaptive component-substitution-based satellite image fusion using partial replacement [5].”
A New Adaptive Component-Substitution-Based Satellite Image Fusion by Using Partial Replacement (2011, methodology): “Therefore, the experimental parameters in establishing δ cause nonstable results since they may be different in each case, and they are arrived at by taking an average of the MS bands or considering connections only between blue and green [5].”