A new intensity-hue-saturation fusion approach to image fusion with a tradeoff parameter

By Myungjin Choi. IEEE Transactions on Geoscience and Remote Sensing, 2006

439 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition, Media Technology

View Paper: https://www.semanticscholar.org/paper/b65f671aba491b0bcd0bb39e1e819b0c0b02f4ac

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In Computer Vision and Pattern Recognition

In Media Technology

Citations in the corpus

A New Adaptive Component-Substitution-Based Satellite Image Fusion by Using Partial Replacement (2011, methodology): “If the modulation coefficient is set too low in order to avoid this problem, the spatial quality of the fused image will decline [6].”
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 ”
Synthesis of Multispectral Images to High Spatial Resolution: A Critical Review of Fusion Methods Based on Remote Sensing Physics (2008, methodology): “Tu et al. [44] proposed an improvement of the work of Choi [42] with an automatic adjustment of the t parameter.”
A review of remote sensing image fusion methods (2016, background): “Component substitution (CS) IHS and different versions of it [39],[42],[43] Fast IHS [44],[45],[46] Generalized IHS [47],[48],[49] Brovey transform (BT) [40] PCA [49],[50],[51] Gram-Schmidt (GS) [41]”
Remote Sensing Image Fusion via Sparse Representations Over Learned Dictionaries (2013, methodology): “The representative component-substitution-based methods are the intensity–hue– saturation (IHS) [3], [4] and the principal component analysis [5].”
Multi-source remote sensing data fusion: status and trends (2010, methodology): “In this way, the optimal weights of the MS bands in synthesising the intensity component and the injection gains could be achieved for single sensor data (Choi 2006 , Garzelli and Nencini 2006 , Gonzales-Audicana et al.”
Advances in multimodal data fusion in neuroimaging: Overview, challenges, and novel orientation (2020, methodology): “Methods like Inten-sity Hue Saturation [215] and Principle Component Analysis (PCA) belong to the category of the spatial domain [216] .”
Comparison of Pansharpening Algorithms: Outcome of the 2006 GRS-S Data-Fusion Contest (2007, methodology): “The GIHS-TP developed at the Advanced Institute of Science and Technology, Daejeon, Korea, is a CS-based method that trades off the performances of GIHS [16] in terms of spectral distortion and spatial enhancement [26].”