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A GIHS-based spectral preservation fusion method for remote sensing images using edge restored spectral modulation
Institution:1. Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, Chongqing 400714, China;2. State Key Laboratory for Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China;3. Chongqing Key Laboratory of Computational Intelligence, Chongqing University of Posts and Telecommunications, Chongqing 400065, China;4. Department of Geography, Hong Kong Baptist University, and Laboratory for High Performance Geo-Computation, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China;1. Centro de Informática, Universidade Federal de Pernambuco, Brazil;2. Departamento de Estatística e Informática, Universidade Federal Rural de Pernambuco, Brazil;1. School of Mechanical Engineering, Hefei University of Technology, Hefei 230009, PR China;2. School of Mechanical Engineering & Division of Environmental and Ecological Engineering, Purdue University, West Lafayette, IN 47907-2088, USA;1. State Key Laboratory of High Field Laser Physics, Shanghai Institute of Optics and Fine Mechanics, Chinese Academy of Sciences, Shanghai 201800, China;2. University of Chinese Academy of Sciences, Beijing 100049, China;3. Department of Materials Chemistry, Ryukoku University, Otsu, Shiga 520-2194, Japan;4. Graduate School of Life Sciences, Ritsumeikan University, Kusatsu, Shiga 525-8577, Japan;5. Advanced Ultrafast Laser Research Center and Brain Science Inspired Life Support Research Center, University of Electro- Communications, 1-5-1, Chofugaoka, Chofu, Tokyo 182-8585, Japan;6. JST, CREST, K’s Gobancho, 7 Gobancho, Chiyoda-ku, Tokyo 102-0076, Japan;7. School of Physical Science and Technology, ShanghaiTech University, Shanghai 201210, China;1. Centre Tecnològic de Telecomunicacions de Catalunya (CTTC/CERCA), Geomatics Division, 08860, Castelldefels, Spain;2. University of Firenze, Department of Earth Sciences. Via Giorgio La Pira 4, 50121, Firenze, Italy;3. Regione Autonoma Valle d‘Aosta, Assessorato Opere pubbliche, Difesa del suolo e edilizia residenziale pubblica. Loc. Amérique, 11020, Quart, Italy;1. School of Internet of Things, Jiangnan University, 1800 Lihu Road, Wuxi 214122, China;2. New Century Shipbuilding Company Limited, Jingjiang, Jiangsu 210004, China;3. College of Electronic and Information Engineering, Suzhou University of Science and Technology, Suzhou 215009, China;1. Department of Mathematics, School of Sciences, South China University of Technology, Guangzhou 510641, China;2. School of Computer Science and Engineering, South China University of Technology, Guangzhou 510641, China
Abstract:High spatial resolution and spectral fidelity are basic standards for evaluating an image fusion algorithm. Numerous fusion methods for remote sensing images have been developed. Some of these methods are based on the intensity–hue–saturation (IHS) transform and the generalized IHS (GIHS), which may cause serious spectral distortion. Spectral distortion in the GIHS is proven to result from changes in saturation during fusion. Therefore, reducing such changes can achieve high spectral fidelity. A GIHS-based spectral preservation fusion method that can theoretically reduce spectral distortion is proposed in this study. The proposed algorithm consists of two steps. The first step is spectral modulation (SM), which uses the Gaussian function to extract spatial details and conduct SM of multispectral (MS) images. This method yields a desirable visual effect without requiring histogram matching between the panchromatic image and the intensity of the MS image. The second step uses the Gaussian convolution function to restore lost edge details during SM. The proposed method is proven effective and shown to provide better results compared with other GIHS-based methods.
Keywords:Image fusion  Generalized intensity–hue–saturation  Edge restored spectral modulation  Spectral distortion  Image quality evaluation  Remote sensing
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