• Journal of Korea Multimedia Society
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• v.17 no.8
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• pp.923-936
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• 2014

Images can be contaminated with different types of noise, for different reasons. The neighborhood averaging and smoothing by image averaging are the classical image processing techniques for noise removal. The classical spatial filtering refers to the aggregate of pixels composing an image and operating directly on these pixels. To reduce or remove effectively noise in image sequences, it usually needs to use noise reduction filter based on space or time domain such as method of spatial or temporal filter. However, the method of spatial filter can generally cause that signals of objects as the target are also blurred. In this paper, we propose temporal filter using the piece-wise quadratic function model and enhancement algorithm of image quality for the performance improvement of target detection and tracking by heterogeneous noise reduction. Image tracking simulation that utilizes real IIR(Imaging Infra-Red) images is employed to evaluate the performance of the proposed image processing algorithm.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.34 no.4
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• pp.413-423
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• 2016

Worldview-3 satellite sensor provides panchromatic image with high-spatial resolution and 8-band multispectral images. Therefore, an image-sharpening technique, which sharpens the spatial resolution of multispectral images by using high-spatial resolution panchromatic images, is essential for various applications of Worldview-3 images based on image interpretation and processing. The existing pansharpening algorithms tend to tradeoff between spectral distortion and spatial enhancement. In this study, we applied six pansharpening algorithms to Worldview-3 satellite imagery and assessed the quality of pansharpened images qualitatively and quantitatively. We also analyzed the effects of time lag for each multispectral band during the pansharpening process. Quantitative assessment of pansharpened images was performed by comparing ERGAS (Erreur Relative Globale Adimensionnelle de Synthèse), SAM (Spectral Angle Mapper), Q-index and sCC (spatial Correlation Coefficient) based on real data set. In experiment, quantitative results obtained by MRA (Multi-Resolution Analysis)-based algorithm were better than those by the CS (Component Substitution)-based algorithm. Nevertheless, qualitative quality of spectral information was similar to each other. In addition, images obtained by the CS-based algorithm and by division of two multispectral sensors were shaper in terms of spatial quality than those obtained by the other pansharpening algorithm. Therefore, there is a need to determine a pansharpening method for Worldview-3 images for application to remote sensing data, such as spectral and spatial information-based applications.

• ETRI Journal
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• v.33 no.4
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• pp.497-505
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• 2011

Image fusion is a technical method to integrate the spatial details of the high-resolution panchromatic (HRP) image and the spectral information of low-resolution multispectral (LRM) images to produce high-resolution multispectral images. The most important point in image fusion is enhancing the spatial details of the HRP image and simultaneously maintaining the spectral information of the LRM images. This implies that the physical characteristics of a satellite sensor should be considered in the fusion process. Also, to fuse massive satellite images, the fusion method should have low computation costs. In this paper, we propose a fast and efficient satellite image fusion method. The proposed method uses the spectral response functions of a satellite sensor; thus, it rationally reflects the physical characteristics of the satellite sensor to the fused image. As a result, the proposed method provides high-quality fused images in terms of spectral and spatial evaluations. The experimental results of IKONOS images indicate that the proposed method outperforms the intensity-hue-saturation and wavelet-based methods.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.33 no.1
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• pp.63-70
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• 2015

An Image fusion, or Pansharpening is a methodology of increasing the spatial resolution of image with low-spatial resolution using high-spatial resolution images. In this paper, we have performed an image fusion of hyperspectral imagery by using panchromatic image with high-spatial resolution, multispectral and hyperspectral images with low-spatial resolution, which had been acquired by ALI and Hyperion of EO-1 satellite sensors. The study has been mainly focused on evaluating performance of fusion process following to the image fusion methodology of the block association, which had applied to ALI and Hyperion dataset by considering spectral characteristics between multispectral and hyperspectral images. The results from experiments have been identified that the proposed algorithm efficiently improved the spatial resolution and minimized spectral distortion comparing with results from a fusion of the only panchromatic and hyperspectral images and the existing block-based fusion method. Through the study in a proposed algorithm, we could concluded in that those applications of airborne hyperspectral sensors and various hyperspectral satellite sensors will be launched at future by enlarge its usages.

• Journal of the Korea Computer Graphics Society
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• v.25 no.3
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• pp.21-29
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• 2019

This paper proposes a novel framework for image fusion of satellite imagery to enhance spatial resolution of the image via structure-texture decomposition. The resolution of the satellite imagery depends on the sensors, for example, panchromatic images have high spatial resolution but only a single gray band whereas multi-spectral images have low spatial resolution but multiple bands. To enhance the spatial resolution of low-resolution images, such as multi-spectral or infrared images, the proposed framework combines the structures from the low-resolution image and the textures from the high-resolution image. To improve the spatial quality of structural edges, the structure image from the low-resolution image is guided filtered with the structure image from the high-resolution image as the guidance image. The combination step is performed by pixel-wise addition of the filtered structure image and the texture image. Quantitative and qualitative evaluation demonstrate the proposed method preserves spectral and spatial fidelity of input images.

• Korean Journal of Remote Sensing
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• v.34 no.2_2
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• pp.377-391
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• 2018

In order to efficiently monitor red tide over a wide range, the need for red tide detection using remote sensing is increasing. However, the previous studies focus on the development of red tide detection algorithm for ocean colour sensor. In this study, we propose the use of multi-sensor to improve the inaccuracy for red tide detection and remote sensing data in coastal areas with high turbidity, which are pointed out as limitations of satellite-based red tide monitoring. The study area were selected based on the red tide information provided by National Institute of Fisheries Science, and spatial fusion and spectral-based fusion were attempted using GOCI image as ocean colour sensor and Landsat OLI image as terrestrial sensor. Through spatial fusion of the two images, both the red tide of the coastal area and the outer sea areas, where the quality of Landsat OLI image was low, which were impossible to observe in GOCI images, showed improved detection results. As a result of spectral-based fusion performed by feature-level and rawdata-level, there was no significant difference in red tide distribution patterns derived from the two methods. However, in the feature-level method, the red tide area tends to overestimated as spatial resolution of the image low. As a result of pixel segmentation by linear spectral unmixing method, the difference in the red tide area was found to increase as the number of pixels with low red tide ratio increased. For rawdata-level, Gram-Schmidt sharpening method estimated a somewhat larger area than PC spectral sharpening method, but no significant difference was observed. In this study, it is shown that coastal red tide with high turbidity as well as outer sea areas can be detected through spatial fusion of ocean colour and terrestrial sensor. Also, by presenting various spectral-based fusion methods, more accurate red tide area estimation method is suggested. It is expected that this result will provide more precise detection of red tide around the Korean peninsula and accurate red tide area information needed to determine countermeasure to effectively control red tide.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.5C
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• pp.706-715
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• 2004

In this paper, to decide the watermark embedding positions and embed the watermark we use the subband tee structure which is presented in the wavelet domain and the edge information in the spatial domain. The significant frequency region is estimated by the subband searching from the higher frequency subband to the lower frequency subband. LH1 subband which has the higher frequency in tree structure of the wavelet domain is divided into 4${\times}$4 submatrices, and the threshold which is used in the watermark embedding is obtained by the blockmatrix which is consists by the average of 4${\times}$4 submatrices. Also the watermark embedding position, Keymap is generated by the blockmatrix for the energy distribution in the frequency domain and the edge information in the spatial domain. The watermark is embedded into the wavelet coefficients using the Keymap and the random sequence generated by LFSR(Linear feedback shift register). Finally after the inverse wavelet transform the watermark embedded image is obtained. the proposed watermarking algorithm showed PSNR over 2㏈ and had the higher results from 2％ to 8％ in the comparison with the previous research for the attack such as the JPEG compression and the general image processing just like blurring, sharpening and gaussian noise.

• 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.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.6
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• pp.555-563
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• 2018

Thermal infrared images have the characteristic of being able to detect objects that can not be seen with the naked eye and have the advantage of easily obtaining information of inaccessible areas. However, TIR (Thermal InfraRed) images have a relatively low spatial resolution. In this study, the applicability of the pansharpening algorithm used for satellite imagery on images acquired by the UAV (Unmanned Aerial Vehicle) was tested. RGB image have higher spatial resolution than TIR images. In this study, pansharpening algorithm was applied to TIR image to create the images which have similar spatial resolution as RGB images and have temperature information in it. Experimental results show that the pansharpening algorithm using the PC1 band and the average of RGB band shows better results for the quantitative evaluation than the other bands, and it has been confirmed that pansharpening results by ATWT (${\grave{A}}$ Trous Wavelet Transform) exhibit superior spectral resolution and spatial resolution than those by HPF (High-Pass Filter) and SFIM (Smoothing Filter-based Intensity Modulation) pansharpening algorithm.

• Journal of the Korea Computer Graphics Society
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• v.11 no.1
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• pp.8-12
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• 2005

본 연구에서는 영상에 간단한 공간 필터를 적용하여 연필 해칭 효과를 갖는 영상을 만들어 내는 방법을 제안한다. 해칭 스타일의 톤 생성을 위하여 모션 블러링을 이용해서 입력 영상에 방향성을 주고, 샤프닝과 블러링으로 연필 해칭 효과를 만들어 낸다. 이렇게 만들어진 영상은 영상 전체에 같은 방향으로 해칭한 것 같은 효과를 가진다. 모션 블러링을 각기 다른 방향으로 적용한 영상들을 합성하면 크로스 해칭의 효과를 만들 수 있다. 여기에 소벨 필터를 사용해서 원본 영상의 에지를 검출해서 함께 합성하여 해칭을 이용한 연필화를 생성한다.