Abstract
The panchromatic sharpening or pansharpening refers to the fusion process of high-resolution panchromatic image and low- resolution multi-spectral images. Modulation Transfer Function (MTF) of satellite sensors has also been used for pansharpening. We investigate the use of Takagi–Sugeno fuzzy systems in MTF-based pansharpening algorithms. Traditional pansharpening schemes can result in spatial and/or spectral distortion during the fusion process. A fuzzy integrated fusion scheme is proposed to overcome this limitation. Spectral dissimilarities between panchromatic and multi-spectral bands are also taken into account. While preserving low-resolution multi-spectral information, Takagi–Sugeno fuzzy is introduced to inject appropriate spatial details in the pansharpened image. The local features of panchromatic image are also exploited to preserve the spatial and spectral content. Experiments conducted on Pl\(\acute{e}\)iades, Spot-5 and WorldView-2 data set demonstrate the superior fusion quality of the proposed scheme.
Similar content being viewed by others
Explore related subjects
Discover the latest articles, news and stories from top researchers in related subjects.References
Aiazzi B, Alparone L, Baronti S, Garzelli A (2002) Context-driven fusion of high spatial and spectral resolution images based on over sampled multiresolution analysis. IEEE Trans Geosci Remote Sens 40(10):2300–2312
Aiazzi B, Alparone L, Baronti S, Garzelli A, Selva M (2006) MTF tailored multiscale fusion of high-resolution MS and Pan imagery. Photogramm Eng Remote Sensing 72(5):591–596
Aiazzi B, Baronti S, Selva M (2007) Improving component substitution pansharpening through multivariate regression of MS+Pan data. IEEE Trans Geosci Remote Sens 45(10):3230–3239
Aiazzi B, Baronti S, Lotti F, Selva M (2009) A comparison between global and context-adaptive pansharpening of multisepctral image. IEEE Geosci Remote Sens Lett 6(2):302–306
Ali SS, Riaz MM, Ghafoor A (2013) Hybrid component substitution and wavelet based image fusion. IEEE Int Conf Acoust Speech Signal Process, Vancouver, Canada, 2498–2502
Ali SS, Riaz MM, Ghafoor A (2014) Fuzzy logic and additive wavelet based panchromatic sharpening. IEEE Geosci Remote Sens Lett 11(1):357–360
Alparone L, Baronti S, Garzelli A, Nencini F (2004) A global quality measurement of pan-sharpened multispectral imagery. IEEE Geosci Remote Sens Lett 1(4):313–317
Alparone L, Wald L, Chanussot J, Thomas C, Gamba P, Bruce LM (2007) Comparison of pansharpening algorithms: outcome of the 2006 GRS-S data-fusion contest. IEEE Trans Geosci Remote Sens 45(10):3012–3021
Alparone L, Aiazzi B, Baronti S, Garzelli A, Nencini F, Selva M (2008) Mutltispectral and panchromatic data fusion assessment without reference. Photogramm Eng Remote Sensing 74(2):193–200
Choi J, Yu K, Kim Y (2011) A new adaptive component-substitution-based satellite image fusion by using partial replacement. IEEE Trans Geosci Remote Sens 49(1):295–309
Gang L, Zhong-liang J, Shao-yuan S (2006) Multiresolution image fusion scheme based on fuzzy region feature. J Zhejiang Univ Sci 7(2):117–122
Hung JC (2014) Robust Kalman filter based on a fuzzy GARCH model to forecast volatility using particle swarm optimization. Soft Comput J 1–9
Khan MM, Alparone L, Chanussot J (2009) Pansharpening quality assessment using the modulation transfer functions of instruments. IEEE Trans Geosci Remote Sens 47(11):3880–3891
Kim Y, Lee C, Han D, Kim Y, Kim Y (2011) Improved additive-wavelet image fusion. IEEE Geosci Remote Sens Lett 8(2):263–267
Kim Y, Eo Y, Kim Y, Kim Y (2011) Generalized IHS-based satellite imagery fusion using spectral response functions. ETRI J 33(4):494–505
Leu FY, Liu JC, Hsu YT, Huang YL (2014) The simulation of an emotional robot implemented with fuzzy logic. Soft Comput J 1–15
Li S, Kwok JT, Wang Y (2001) Combination of images with diverse focuses using the spatial frequency. Inf Fusion 2:169–176
Ling Y, Ehlers M, Usery L, Madden M (2007) FFT-enhanced IHS transform method for fusing high-resolution satellite images. ISPRS J Photogramm Remote Sens 61(6):381–392
Nunez J, Otazu X, Fors O, Prades A, Pala V, Arbiol R (1999) Multiresolution-based image fusion with additive wavelet decomposition. IEEE Trans Geosci Remote Sens 37(3):1204–1211
Otazu X, Audicana MG, Fors O, Nunez J (2005) Introduction of sensor spectral response into image fusion method. Application to wavelet-based methods. IEEE Trans Geosci Remote Sens 43(10):2376–2385
Padwick C, Deskevich M, Pacifici F, Smallwood S (2010) WorldView-2 pan-sharpening. ASPRS Ann Conf, San Diego, California
Riaz MM, Ghafoor A (2013) Spectral and textural weighting using Takagi–Sugeno fuzzy system for through wall image enhancement. Prog Electromagn Res B 48:115–130
Seng C, Bouzerdoum A, Amin M, Phung S (2013) Two-Stage fuzzy fusion with applications to through-the-wall radar imaging. IEEE Trans Geosci Remote Sens Lett 10(4):687–691
Sohn M, Jeong S, Lee HJ (2014) Case-based context ontology construction using fuzzy set theory for personalized service in a smart home environment. Soft Comput J 1–14
Takagi T, Sugeno M (1985) Fuzzy identification of systems and its applications to modeling and control. IEEE Trans Syst Man Cybern 15:116–132
Thomas C, Ranchin T, Wald L, Chanussot J (2008) Synthesis of multispectral images to high spatial resolution: a critical review of fusion methods based on remote sensing physics. IEEE Trans Geosci Remote Sens 46(5):1301–1312
Tu TM, Huang PS, Hung CL, Chang CP (2004) A fast intensityhuesaturation fusion technique with spectral adjustment for IKONOS imagery. IEEE Geosci Remote Sens Lett 1(4):309–312
Wald L (2000) Quality of high resolution synthesised images: is there a simple criterion. Fusion Earth Data Merg Point Meas Raster Maps Remote Sense Images 99–103
Wang Z, Bovik AC (2002) A universal image quality index. IEEE Signal Process Lett 9(3):81–84
Wang Z, Ziou D, Armenakis C, Li D, Li Q (2005) A comparative analysis of image fusion methods. IEEE Trans Geosci Remote Sens 43(6):1391–1402
Zhang DG, Kang X, Wang J (2012) A novel image de-noising method based on spherical coordinates system. EURASIP J Adv Signal Process 1–10
Zhang Y (2008) Methods for image fusion quality assessment—a review, comparison and analysis. Int Arch Photogramm Remote Sens Spat Inf Sci, Beijing, China, XXXVII:1101–1109
Zhang DG, Zhang XD (2012) Design and implementation of embedded un-interruptible power supply system (EUPSS) for web-based mobile application. Enterp Inf Syst 6(4):473–489
Zhang DG (2012) A new approach and system for attentive mobile learning based on seamless migration. Appl Intell 36(1):75–89
Zhang DG, Li G, Pan Z (2014) An energy-balanced routing method based on forward-aware factor for wireless sensor network. IEEE Trans Industr Inform 10(1):766–773
Zhu M, Yang Y (2008) A new image fusion algorithm based on fuzzy logic. Intell Comput Technol Autom 2:83–86
Author information
Authors and Affiliations
Corresponding author
Additional information
Communicated by Y.-S. Ong.
Rights and permissions
About this article
Cite this article
Ali, S.S., Riaz, M.M., Ghafoor, A. et al. Takagi–Sugeno Fuzzy System and MTF-based Panchromatic Sharpening. Soft Comput 20, 4695–4708 (2016). https://doi.org/10.1007/s00500-014-1526-z
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00500-014-1526-z