• IEIE Transactions on Smart Processing and Computing
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• v.5 no.6
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• pp.403-417
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• 2016

This paper reviews recent published works dealing with the application of wavelets to image processing based on multiresolution analysis. After revisiting the basics of wavelet transform theory, various applications of wavelets and multiresolution analysis are reviewed, including image denoising, image enhancement, super-resolution, and image compression. In addition, we introduce the concept and theory of quaternion wavelets for the future advancement of wavelet transform and quaternion multiresolution applications.

• Journal of the Korean Association of Geographic Information Studies
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• v.4 no.3
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• pp.61-70
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• 2001

This paper presents a new method to extract semi-automatically roads from high spatial resolution satellite imagery. This method is based both on wavelet transform and on multiresolution analysis combined in the "$\grave{a}$ trous" algorithm. As an urban road network consists on different classes of streets, multiresolution processing allows to extract the streets class by class. The method was applied to a KVR-1000 image on a part of Busan Metropolitan City. The method was carried out for the road extraction of three different widths and it succeeded in extracting good fitted strips. The accuracy analysis for three types of streets was also performed. The overall accuracy in 4 pixels of width is 80.5%. The result suggests that this method can be used to update road networks in the studied urban network. In summary, the multiresolution approach based on the wavelet transform, used in this study, is regarded as one of effective methods to extract urban road network from high spatial resolution satellite images.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.40 no.2
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• pp.1-10
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• 2003

This paper presents an efficient method for image segmentation based on a multiresolution application of a wavelet transform and watershed segmentation algorithm. The procedure toward complete segmentation consists of four steps: pyramid representation, image segmentation, region merging and region projection. First, pyramid representation creates multiresolution images using a wavelet transform. Second, image segmentation segments the lowest-resolution image of the pyramid using a watershed segmentation algorithm. Third, region merging merges the segmented regions using the third-order moment values of the wavelet coefficients. Finally, the segmented low-resolution image with label is projected into a full-resolution image (original image) by inverse wavelet transform. Experimental results of the presented method can be applied to the segmentation of noise or degraded images as well as reduce over-segmentation.

• Journal of Korean Society for Geospatial Information Science
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• v.12 no.2 s.29
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• pp.61-66
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• 2004

By the advent of the high-resolution Satellite imagery, there are increasing needs in image mosaicking technology which can be applied to various application fields such as GIS(Geographic Information system). To mosaic images, various methods such as image matching and histogram modification are needed. In this study, automated image mosaicking is performed using image matching method based on the multi-resolution wavelet analysis(MWA). Specifically, both area based and feature based matching method are embedded in the multi-resolution wavelet analysis to construct seam line.; seam points are extracted then polygon clipping method are applied to define overlapped area of two adjoining images. Before mosaicking, radiometric correction is proceeded by using histogram matching method. As a result, mosaicking area is automatically extracted by using polygon clipping method. Also, seamless image is acquired using multi-resolution wavelet analysis.

• Journal of Korean Society for Geospatial Information Science
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• v.10 no.5 s.23
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• pp.53-65
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• 2002

The most widespread techniques for DEM generation are stereoscopy for optical sensor images and SAR interferometry(InSAR) for SAR images. These techniques suffer from certain sensor and processing limitations, which can be overcome by the synergetic use of both sensors and DEMs respectively. This study is associated with improvements of accuracy with consistency of image's characteristics between two different DEMs coming from stereoscopy for the optical images and interferometry for SAR images. The MWD(Multiresolution Wavelet Decomposition) and HPF(High-Pass Filtering), which take advantage of the complementary properties of SAR and stereo optical DEMs, will be applied for the fusion process. DEM fusion is tested with two sets of SPOT and ERS-l/-2 satellite imagery and for the analysis of results, DEM generated from digital topographic map(1 to 5000) is used. As a result of an integration of DEMs, it can more clearly portray topographic slopes and tilts when applying the strengths of DEM of SAR image to DEM of an optical satellite image and in the case of HPF, the resulting DEM.

• Journal of Korean Society for Geospatial Information Science
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• v.10 no.5 s.23
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• pp.45-51
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• 2002

The goal of image merging techniques are to enhance the resolution of low-resolution images using the detail information of the high-resolution images. Among the several image merging methods, wavelet-based image merging techniques have the advantages of efficient decorrelation of image bands and time-scale analysis. However, they have no regard for spatial information between the bands. In other words, multiresolution data merging methods merge the same information-the detail information of panchromatic image-with other band images, without considering specific characteristics. Therefore, a merged image contains much unnecessary information. In this paper, we discussed this 'mixing' effect and, proposed a method to classify the detail information of the panchromatic image according to the spatial and spectral characteristics, and to minimize distortion of the merged image.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2014.06a
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• pp.226-229
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• 2014

본 논문은 효과적인 열화영상의 복원을 위해 Multiresolution Bilateral Filter (MBF) 기반의 구간적 노이즈 분석을 제안한다. 기존의 MBF 알고리즘은 최적화되지 않은 노이즈 추정 값을 중첩적으로 사용하다보니 over smoothing 현상이 발생되는 결과가 도출되기도 하였다. 이에 따른 보완점으로 열화영상 내 전체 화소를 일정한 블록 단위의 영역으로 나누어, 영상특성을 최대한 보존하며 노이즈제거를 진행하기 위해 블록 단위의 영역 내에서 노이즈 추정을 위한 파라미터를 추가한다. 실험을 통해 제안된 알고리즘이 노이즈 추정을 수행하여 얻어진 노이즈의 분산 값을 보다 정확히 추정하였고, 이로 인하여 향상된 노이즈 제거 영상 획득이 가능함을 확인할 수 있었다.

• Korean Journal of Remote Sensing
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• v.20 no.3
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• pp.207-214
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• 2004

This study focused on providing a methodology to utilize temporal information obtained from remotely sensed data for monitoring a wide variety of targets on the earth's surface. Generally, a methodology in understanding of global changes is composed of mapping, quantifying, and monitoring changes in the physical characteristics of land cover. The selected processing and analysis technique affects the quality of the obtained information. In this research, feature extraction methodology is proposed based on segmentation. It requires a series of processing of multitempotal images: preprocessing of geometric and radiometric correction, image subtraction/thresholding technique, and segmentation/thresholding. It results in the mapping of the change-detected areas. Here, the appropriate methods are studied for each step and especially, in segmentation process, a method to delineate the exact boundaries of features is investigated in multiresolution framework to reduce computational complexity for multitemporal images of large size.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.724-726
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• 2003

Currently available image fusion methods are not efficient for fusing the Landsat 7 images. Significant color distortion is one of the major problems. In this paper, using the well-known wavelet based method for data fusion between high-resolution panchromatic and low-resolution multispectral satellite images, we performed Landsat 7 image fusion. Based on the experimental results obtained from this study, we analyzed some reasons for color distortion. A new approach using the biorthogonal wavelets based method for data fusion is presented. This new method has reached an optimum fusion result - with the same spectral resolution as the multispectral image and the same spatial resolution as the panchromatic image with minimum artifacts.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.1
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• pp.150-156
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• 2007

Noise is generated by several causes, when signal is processed. Hence, it generates error in the process of data transmission and decreases recognition ratio of image and speech data. Therefore, after eliminating those noises, a variety of methods for reconstructing the signal have been researched. Recently, wavelet transform which has time-frequency localization and is possible for multiresolution analysis is applied to many fields of technology. Then threshold-and correlation-based methods are proposed for removing noise. But, conventional methods accept a lot of noise as an edge and are impossible to remove the additive white Gaussian noise (AWGN) and the impulse noise at the same time. Therefore, in this paper we proposed new wavelet-based algorithm for reconstructing degraded signal by noise and compared it with conventional methods.