• Journal of the Korean Institute of Navigation
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• v.21 no.1
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• pp.119-128
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• 1997

Nowadays, many satellites regularly produce digital multispectral images of the earth's surface. Multispectral images may be displayed as color pictures by selecting three components for assignment to the primary colors. It is desired to enhance these images to generate a display picture that are representativde of their features. in this paper, a false color image processing algorithm is proposed for the purpose of enchancement of the multispectral images based on the human perception. The mean of each primary component is transformed to equalo. Intensity and saturation are enhanced by modified piecewise linear contrast strectching and saturation enhancement method. The proposed method has been successfully applied the LANDSAT TM image and shows good enhancement.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.620-624
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• 2007

Recently, Gonzalez-Audicana et al. proposed the substitute wavelet intensity (SWI) method which provided a solution based on the intensity-hue-saturation (IHS) method for the fusing of panchromatic (PAN) and multispectral (MS) images. Although the spectral quality of the fused MS images is enhanced, this method is not efficient enough to quickly merge massive volumes of data from satellite. To overcome this problem, we introduce a new SWI method based on a fast IHS transform to implement efficiently as an alternative procedure. In addition, we show that the method is well applicable for fusing IKONOS PAN with MS images.

• Korean Journal of Remote Sensing
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• v.23 no.5
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• pp.347-353
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• 2007

Recently, $Gonz\acute{a}lez-Aud\acute{i}cana$ et al. proposed the substitute wavelet intensity(SWI) method which provided a solution based on the intensity-hue-saturation(IHS) method for the fusing of panchromatic(PAN) and multispectral(MS) images. Although the spectral quality of the fused MS images is enhanced, this method is not efficient enough to quickly merge massive volumes of data from satellite. To overcome this problem, we introduce a new SWI method based on a fast IHS transform to implement efficiently as an alternative procedure. In addition, we show that the method is well applicable for fusing IKONOS PAN with MS images.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.3
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• pp.1633-1649
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• 2017

In remote sensing image processing, the traditional fusion algorithm is based on the Intensity-Hue-Saturation (IHS) transformation. This method does not take into account the texture or spectrum information, spatial resolution and statistical information of the photos adequately, which leads to spectrum distortion of the image. Although traditional solutions in such application combine manifold methods, the fusion procedure is rather complicated and not suitable for practical operation. In this paper, an improved IHS transformation fusion algorithm based on the local variance weighting scheme is proposed for remote sensing images. In our proposal, firstly, the local variance of the SPOT (which comes from French "Systeme Probatoire d'Observation dela Tarre" and means "earth observing system") image is calculated by using different sliding windows. The optimal window size is then selected with the images being normalized with the optimal window local variance. Secondly, the power exponent is chosen as the mapping function, and the local variance is used to obtain the weight of the I component and match SPOT images. Then we obtain the I' component with the weight, the I component and the matched SPOT images. Finally, the final fusion image is obtained by the inverse Intensity-Hue-Saturation transformation of the I', H and S components. The proposed algorithm has been tested and compared with some other image fusion methods well known in the literature. Simulation result indicates that the proposed algorithm could obtain a superior fused image based on quantitative fusion evaluation indices.

• Korean Journal of Geomatics
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• v.3 no.1
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• pp.59-65
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• 2003

The merging of different scales or multi-sensor image data is becoming a widely used procedure of the complementary nature of various data sets. Ideally, the merging method should not distort the characteristics of the high-spatial and high-spectral resolution data used. To present an effective merging method for survey of reclaimed land using the high-resolution (6.6 m) Electro-Optical Camera (EOC) panchromatic image of the first Korea Multi-Purpose Satellite 1 (KOMPSA T-l) and the multispectral Moderate Resolution Imaging Spectroradiometer (MODIS) image data, this paper compares the results of Intensity Hue Saturation (IHS) and Principal Component Analysis (PCA) methods. The comparison is made by statistical and visual evaluation of three-color combination images of IHS and PCA results based on spatial and spectral characteristics. The use of MODIS bands 1, 2, and 3 with a contrast stretched EOC panchromatic image as a substitute for intensity was found to be particularly effective in this study.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2003.04a
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• pp.171-180
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• 2003

The merging of different scales or multi-sensor image data is becoming a widely used procedure of the complementary nature of various data sets. Ideally, the merging method should not distort the characteristics of the high-spatial and high-spectral resolution data used. To present an effective merging method for survey of reclaimed land, this paper compares the results of Intensity Hue Saturation (IHS), Principal Component Analysis (PCA), Color Normalized(CN) and High Pass Filter(HPF) methods used to merge the information contents of the high-resolution (6.6 m) Electro-Optical Camera (EOC) panchromatic image of the first Korea Multi-Purpose Satellite 1 (KOMPSAT-1) and the multi-spectral Moderate Resolution Imaging Spectroradiometer (MODIS) image data. The comparison is made by visual evaluation of three-color combination images of IHS, PCA, CN and HPF results based on spatial and spectral characteristics. The use of a contrasted EOC panchromatic image as a substitute for intensity in merged images with MODIS bands 1, 2 and 3 was found to be particularly effective in this study.

• 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.

• Korean Journal of Remote Sensing
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• v.14 no.2
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• pp.149-164
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• 1998

The main object of this study was to prove the effectiveness of different merging methods by using the high resolution IRS(Indian Remote Sensing Satellite)-1C panchromatic data and the multispectral Landsat TM data. The five methods used to merging the information contents of each of the satellite data were the intensity-hue-saturation(IHS), principal component analysis(PCA), high pass filter(HPF), ratio enhancement method and look-up-table(LUT) procedures. Two measures are used to evaluate the merging method. These measures include visual inspection and comparisons of the mean, standard deviation and root mean square error between merged image and original image data values of each band. The ratio enhancement method was well preserved the spectral characteristics of the data. From visual inspection, PCA method provide the best result, HPF next, ratio enhancement, IHS and LUT method the worst for the preservation of spatial resolution.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.5
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• pp.103-108
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• 1993

An image can be largely corrupted by the ambient illuminant, so that the image enhancement to restory natural color without respect to the ambient illuminant is needed. It this paper, a new color image enhancement technique based on color constancy is proposed. To enhance the image quality, higher volues of contrast and saturation are preferred, but their excessive values make an image unnatural. Since the color constancy processing preserves only hue, while reducing the dynamic range of lightness and saturation,the technique is needed in order to compensate this phenomenon. The proposed method transforms and increases lightness and saturation simultaneously to avoid the complexity in the related transformation by analyzing the relationship between the RGB and modified IHS coordinate system.

• 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.