• Title/Summary/Keyword: Fusion Image

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An Adaptive FIHS Fusion Using Spatial and Spectral Band Characteristics of Remote Sensing Image (위성 영상의 공간 및 분광대역 특성을 활용한 적응 FIHS 융합)

  • Seo, Yong-Su;Kim, Joong-Gon
    • Journal of the Korean Association of Geographic Information Studies
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    • v.12 no.4
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    • pp.125-135
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    • 2009
  • Owing to its fast computing capability for fusing images, the FIHS(Fast Intensity Hue Saturation) fusion is widely used for fusion purposes. However, the FIHS fusion also distorts color in the same way such as the IHS(Intensity Hue Saturation) fusion technique. In this paper, a FIHS fusion technique(FIHS-BR) which reduces color distortion by using the ratio of each spectral band and an adaptive FIHS fusion(FIHS-SABR) using spatial information and the ratio of each spectral band are proposed. The proposed FIHS-BR fusion reduces color distortion by adding different spatial detail improvement values for each spectral band. The spatial detail improvement values are derived from the ratio of spectral band. And the proposed FIHS-SABR fusion reduces more color distortion by readjusting the spatial detail improvement values for each spectral band according to the ratio of the spectral bands. The spatial detail improvement values are derived adaptively from the characteristics of spatial information of the local image. To evaluate the performance of the proposed FIHS-BR fusion and FIHS-SABR fusion, a computer simulation is performed for IKONOS remote sensing image. Results from the experiments show that the proposed methods have less color distortion for the forest regions which reveal severe color distortion in the traditional FIHS fusion. From the evaluation results of the characteristics of spectral information for fused image, we show that the proposed methods have best results.

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Analysis of Image Integration Methods for Applying of Multiresolution Satellite Images (다중 위성영상 활용을 위한 영상 통합 기법 분석)

  • Lee Jee Kee;Han Dong Seok
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.22 no.4
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    • pp.359-365
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    • 2004
  • Data integration techniques are becoming increasing1y important for conquering a limitation with a single data. Image fusion which improves the spatial and spectral resolution from a set of images with difffrent spatial and spectral resolutions, and image registration which matches two images so that corresponding coordinate points in the two images correspond to the same physical region of the scene being imaged have been researched. In this paper, we compared with six image fusion methods(Brovey, IHS, PCA, HPF, CN, and MWD) with panchromatic and multispectral images of IKONOS and developed the registration method for applying to SPOT-5 satellite image and RADARSAT SAR satellite image. As the result of tests on image fusion and image registration, we could find that MWD and HPF methods showed the good result in term of visual comparison analysis and statistical analysis. And we could extract patches which depict detailed topographic information from SPOT-5 and RADARSAT and obtain encouraging results in image registration.

Pan-Sharpening Algorithm of High-Spatial Resolution Satellite Image by Using Spectral and Spatial Characteristics (영상의 분광 및 공간 특성을 이용한 고해상도 위성영상 융합 알고리즘)

  • Choi, Jae-Wan;Kim, Yong-Il
    • Journal of Korean Society for Geospatial Information Science
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    • v.18 no.2
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    • pp.79-86
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    • 2010
  • Generally, image fusion is defined as generating re-organized image by merging two or more data using special algorithms. In remote sensing, image fusion technique is called as Pan-sharpening algorithm because it aims to improve the spatial resolution of original multispectral image by using panchromatic image of high-spatial resolution. The pan-sharpened image has been an important task due to various applications such as change detection, digital map creation and urban analysis. However, most approaches have tended to distort the spectral information of the original multispectral data or decrease the spatial quality compared with the panchromatic image. In order to solve these problems, a novel pan-sharpening algorithm is proposed by considering the spectral and spatial characteristics of multispectral image. The algorithm is applied to the KOMPSAT-2 and QuickBird satellite image and the results showed that our method can improve the spectral/spatial quality compared with the existing fusion algorithms.

Spectral Quality Enhancement of Pan-Sharpened Satellite Image by Using Modified Induction Technique (수정된 영상 유도 기법을 통한 융합영상의 분광정보 향상 알고리즘)

  • Choi, Jae-Wan;Kim, Hyung-Tae
    • Journal of Korean Society for Geospatial Information Science
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    • v.16 no.3
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    • pp.15-20
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    • 2008
  • High-spatial resolution remote sensing satellites (IKONOS-2, QuickBird and KOMPSAT-2) have provided low-spatial resolution multispectral images and high-spatial resolution panchromatic images. Image fusion or Pan-sharpening is a very important in that it aims at using a satellite image with various applications such as visualization and feature extraction through combining images that have a different spectral and spatial resolution. Many image fusion algorithms are proposed, most methods could not preserve the spectral information of original multispectral image after image fusion. In order to solve this problem, modified induction technique which reduce the spectral distortion of fused image is developed. The spectral distortion is adjusted by the comparison between the spatially degraded pan-sharpened image and original multispectral image and our algorithm is evaluated by QuickBird satellite imagery. In the experiment, pan-sharpened image by various methods can reduce spectral distortion when our algorithm is applied to the fused images.

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Two Scale Fusion Method of Infrared and Visible Images Using Saliency and Variance (현저성과 분산을 이용한 적외선과 가시영상의 2단계 스케일 융합방법)

  • Kim, Young Choon;Ahn, Sang Ho
    • Journal of Korea Multimedia Society
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    • v.19 no.12
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    • pp.1951-1959
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    • 2016
  • In this paper, we propose a two-scale fusion method for infrared and visible images using saliency and variance. The images are separated into two scales respectively: a base layer of low frequency component and a detailed layer of high frequency component. Then, these are synthesized using weight. The saliencies and the variances of the images are used as the fusion weights for the two-scale images. The proposed method is tested on several image pairs, and its performance is evaluated quantitatively by using objective fusion metrics.

Image Fusion and Evaluation by using Mapping Satellite-1 Data

  • Huang, He;Hu, Yafei;Feng, Yi;Zhang, Meng;Song, DongSeob
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.31 no.6_2
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    • pp.593-599
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    • 2013
  • China's Mapping Satellite-1, developed by the China Aerospace Science and Technology Corporation (CASC), was launched in three years ago. The data from Mapping Satellite-1 are able to use for efficient surveying and geometric mapping application field. In this paper, we fuse the panchromatic and multispectral images of Changchun area, which are obtained from the Mapping Satellite-1, the one that is the Chinese first transmission-type three-dimensional mapping satellite. The four traditional image fusion methods, which are HPF, Mod.IHS, Panshar and wavelet transform, were used to approach for effectively fusing Mapping Satellite-1 remote sensing data. Subsequently we assess the results with some commonly used methods, which are known a subjective qualitative evaluation and quantitative statistical analysis approach. Consequently, we found that the wavelet transform remote sensing image fusion is the optimal in the degree of distortion, the ability of performance of details and image information availability among four methods. To further understand the optimal methods to fuse Mapping Satellite-1 images, an additional study is necessary.

Segment-based Image Classification of Multisensor Images

  • Lee, Sang-Hoon
    • Korean Journal of Remote Sensing
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    • v.28 no.6
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    • pp.611-622
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    • 2012
  • This study proposed two multisensor fusion methods for segment-based image classification utilizing a region-growing segmentation. The proposed algorithms employ a Gaussian-PDF measure and an evidential measure respectively. In remote sensing application, segment-based approaches are used to extract more explicit information on spatial structure compared to pixel-based methods. Data from a single sensor may be insufficient to provide accurate description of a ground scene in image classification. Due to the redundant and complementary nature of multisensor data, a combination of information from multiple sensors can make reduce classification error rate. The Gaussian-PDF method defines a regional measure as the PDF average of pixels belonging to the region, and assigns a region into a class associated with the maximum of regional measure. The evidential fusion method uses two measures of plausibility and belief, which are derived from a mass function of the Beta distribution for the basic probability assignment of every hypothesis about region classes. The proposed methods were applied to the SPOT XS and ENVISAT data, which were acquired over Iksan area of of Korean peninsula. The experiment results showed that the segment-based method of evidential measure is greatly effective on improving the classification via multisensor fusion.

Fusion of 3D Cardiac SPECT and 64-Channel-CT Angiography Using Personal Computer in Functionally Relevant Coronary Artery Stenosis (개인용 컴퓨터를 이용한 기능 유관성 관상동맥 협착증의 삼차원 심장스펙트 사진과 64채널 전산화 단층 혈관촬영사진과의 융합)

  • Bahk, Yong-Whee
    • Nuclear Medicine and Molecular Imaging
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    • v.41 no.3
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    • pp.252-254
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    • 2007
  • Image fusion is fast catching attention as Wagner pointed out in his 2006 version of the recent progress and development presented at the annual meeting of Society of Nuclear Medicine. Prototypical fusion of bone scan and radiograph was already attempted at in 1961 when Fleming et al. published an article on strontium-85 bone scan. They simply superimposed dot scan on radiograph enabling simultaneous assessment of altered bone metabolism and local bone anatomy. Indeed the parallel reading of images of bone scan and radiography, CT, MRI or ultrasonography has been practiced in nuclear medicine long since. It is fortunate that recent development of computer science and technology along with the availability of refined CT and SPECT machines has permitted us to open a new avenue to digitally produce precise fusion image so that they can readily be read, exchanged and disseminated using internet. Ten years ago fusion was performed using Bresstrahlung SPECT/CT and it is now achievable by PET/CT and SPECT/CT software and SPECT/CT hardware. The merit of image fusion is its feasibility of reliable assessment of morphological and metabolic change. It is now applicable not only to stationary organs such as brain and skeleton but also to moving organs such as the heart, lung and stomach. Recently, we could create useful fusion image of cardiac SPECT and 64-channel CT angiograph. The former provided myocardial metabolic profile and the latter vascular narrowing in two patients with coronary artery stenosis and myocardial ischemia. Arterial stenosis was severe in Case 1 and mild in Case 2.

Comparison of Image Fusion Methods to Merge KOMPSAT-2 Panchromatic and Multispectral Images (KOMPSAT-2 전정색영상과 다중분광영상의 융합기법 비교평가)

  • Oh, Kwan-Young;Jung, Hyung-Sup;Lee, Kwang-Jae
    • Korean Journal of Remote Sensing
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    • v.28 no.1
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    • pp.39-54
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    • 2012
  • The objective of this study is to propose efficient data fusion techniques feasible to the KOMPSAT-2 satellite images. The most widely used image fusion techniques, which are the high-pass filter (HPF), the intensity-hue-saturation-based (modified IHS), the pan-sharpened, and the wavelet-based methods, was applied to four KOMPSAT - 2 satellite images having different regional and seasonal characteristics. Each fusion result was compared and analyzed in spatial and spectral features, respectively. Quality evaluation of image fusion techniques was performed in both quantitative and visual analysis. The quantitative analysis methods used for this study were the relative global dimensional error (spatial and spectral ERGAS), the spectral angle mapper index (SAM), and the image quality index (Q4). The results of quantitative and visual analysis indicate that the pan-sharpened method among the fusion methods used for this study relatively has the suitable balance between spectral and spatial information. In the case of the modified IHS method, the spatial information is well preserved, while the spectral information is distorted. And also the HPF and wavelet methods do not preserve the spectral information but the spatial information.

A Novel Multi-focus Image Fusion Technique Using Directional Multiresolution Transform (방향성 다해상도 변환을 사용한 새로운 다중초점 이미지 융합 기법)

  • Park, Dae-Chul;Atole, Ronnel R.
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.9 no.4
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    • pp.59-68
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    • 2009
  • This paper addresses a hybrid multi-focus image fusion scheme using the recent curvelet transform constructions. Hybridization is obtained by combining the MS fusion rule with a novel "copy" method. The proposed scheme use MS rule to fuse the m most significant terms in spectrum of an image at each decomposition level. The scheme is dubbed in this work as m-term fusion in adherence to its use of the MSC (most significant coefficients) in the transform set at any given scale, orientation, and translation. We applied the edge-sensitive objective quality measure proposed by Xydeas and Petrovic to evaluate the method. Experimental results show that the proposed scheme is a potential alternative to the redundant, shift-invariant Dual-Tree Complex Wavelet transforms. In particular, it was confirmed that a 50% m-term fusion produces outputs with no visible quality degradation.

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