• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2003.04a
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• pp.255-259
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• 2003

본 연구에서는 고해상도 위성 영상에 관한 압축을 연구하였다. 위성영상은 많은 픽셀 정보와 이루어져 있기 때문에 빠른 영상처리와 데이터 보관을 위해서 압축이 필수적이다. 특히 영상압축시 도로정보와 건물, 산림, 지형 등의 특징을 왜곡을 최소화하여 압축하여야 한다. 따라서는 본 연구에서는 함수공간에서 영상 압축이 가능한 웨이브렛을 기반하여 위성 영상의 압축기법을 제안하였으며, 일반적인 정지영상 압축 기법인 JPEG과의 압축성능을 분석하였다. 그 결과 웨이브렛 압축기법이 JPEG보다 1/10 이상의 압축 성능을 보였다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.6 no.6
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• pp.980-985
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• 2002

In this paper, we analyzed satellite image with a high resolution compression performance. We need much time in a fast processing on vast satellite image pixel data. On compressing and decompressing, we should keep the information about road, building, forest, etc. In conclusion, we did analyze and compare the performance of compression and decompression for JPEG and WSQ(wavelet scalar quantization) method. As a result, we knew that WSQ was more efficient than JPEG.

• Journal of the Korean earth science society
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• v.32 no.6
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• pp.575-585
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• 2011

The effect of wavelet pair choice in the compression of the satellite images is studied. There is a trade-off between compression rate and perception quality. The encoding ratio is used to express the compression rate, and Peak Signal-to-Noise Ratio (PSNR) is also used for the perceptional performance. The PSNR and the encoding ratio are not matched well for the images with various wavelet pairs, but the tendency is remarkable. It is hard to find the pattern of PSNR for sampled images. On the other hand, there is a pattern of the variation range of the encoding ratio for each image. The satellite images have larger values of the encoding ratio than those of nature images (close range images). Depending on the wavelet pairs, the PSNR and the encoding ratio vary as much as 13.2 to 21.6% and 16.8 to 45.5%, respectively for each image. For Synthetic Aperture Radar (SAR) images the encoding ratio varies from 16 to 20% while for the nature images it varies more than 40% depending on the choice of wavelet pairs. The choice of wavelet for the compression affects the nature images more than the satellite images. With the indices such as the PSNR and the encoding ratio, the satellite images are less sensitive to the choice of wavelet pairs. A new index, energy concentration ratio (ECR) is proposed to investigate the effect of wavelet choice on the satellite image compression. It also shows that the satellite images are less sensitive than the nature images. Nevertheless, the effect of wavelet choice on the satellite image compression varies at least 10% for all three kinds of indices. However, the important of choice of wavelet pairs cannot be ignored.

• Journal of the Korean Association of Geographic Information Studies
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• v.3 no.1
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• pp.1-11
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• 2000

The hybrid coding algorithm for multi-spectral image obtained from satellite is discussed. As the spatial and spectral resolution of satellite image are rapidly increasing, there are enormous amounts of data to be processed for computer processing and data transmission. Therefore an efficient coding algorithm is essential for multi-spectral image processing. In this paper, VQ(vector quantization), quadtree decomposition, and DCT(discrete cosine transform) are combined to compress the multi-spectral image. VQ is employed for predictive coding by using the fact that each band of multi-spectral image has the same spatial feature, and DCT is for the compression of residual image. Moreover, the image is decomposed into quadtree structure in order to allocate the data bit according to the information content within the image block to improve the coding efficiency. Computer simulation on Landsat TM image shows the validity of the proposed coding algorithm.

• Journal of Astronomy and Space Sciences
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• v.13 no.2
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• pp.198-209
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• 1996

In this paper, we present an image compression algorithm that is capable of significantly reducing the vast mount of information contained in multispectral images. The developed algorithm exploits the spectral and spatial correlations found in multispectral images. The scheme encodes the difference between images after contrast/brightness equalization to remove the spectral redundancy, and utilizes a two-dimensional wavelet trans-form to remove the spatial redundancy. The transformed images are than encoded by hilbert-curve scanning and run-length-encoding, followed by huffman coding. We also present the performance of the proposed algorithm with KITSAT-1 image as well as the LANDSAT MultiSpectral Scanner data. The loss of information is evaluated by peak signal to noise ratio (PSNR) and classification capability.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.1B
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• pp.120-127
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• 2000

In this paper, we propose multispectral image compression using classified interband prediction and vector quantization in wavelet domain. This method classifies each region considering reflection characteristics of each band in image data. In wavelet domain, we perform the classified intraband VQ to remove intraband redundancy for a reference band image that has the lowest spatial variance and the best correlation with other band. And in wavelet domain, we perform the classifled interband prediction to remove interband redundancy for the remaining bands. Then error wavelet coefficients between original image and predicted image are intraband vector quantized to reduce prediction error. Experiments on remotely sensed satellite image show that coding efficiency of theproposed method is better than that of the conventional method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.10 no.2
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• pp.93-103
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• 1985

The digital signal processing technique by bandwidth compression has been grown up ragidly owing to integrated circuit developments. In this project, we have proposed the Lee Weighted Hadamard (LWH) transform which retains the main properties of Hadamard matirx. The LWH matrix was weighted in the center of the spatial domain. The human visual of the mid spatial are emphasized more than the low and high spatial frequencies. The fast algorithms of the LWH transform has been studied for hardware realization. The result of this project are availabel to airplane photograph, X-Ray, CATV and the artificial satellite of the digital image processing.

• Korean Journal of Remote Sensing
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• v.37 no.6_1
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• pp.1657-1667
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• 2021

Anthropogenic activities and natural processes have been causes of land subsidence which is sudden sinking or gradual settlement of the earth's solid surface. Mexico City, the capital of Mexico, is one of the most severe land subsidence areas which are resulted from excessive groundwater extraction. Because groundwater is the primary water resource occupies almost 70% of total water usage in the city. Traditional terrestrial observations like the Global Navigation Satellite System (GNSS) or leveling survey have been preferred to measure land subsidence accurately. Although the GNSS observations have highly accurate information of the surfaces' displacement with a very high temporal resolution, it has often been limited due to its sparse spatial resolution and highly time-consuming and high cost. However, space-based synthetic aperture radar (SAR) interferometry has been widely used as a powerful tool to monitor surfaces' displacement with high spatial resolution and high accuracy from mm to cm-scale, regardless of day-or-night and weather conditions. In this paper, advanced interferometric approaches have been applied to get a time-series of land subsidence of Mexico City using four-year-long twenty ALOS PALSAR L-band observations acquired from Feb-11, 2007 to Feb-22, 2011. We utilized persistent scatterer interferometry (PSI) and small baseline subset (SBAS) techniques to suppress atmospheric artifacts and topography errors. The results show that the maximum subsidence rates of the PSI and SBAS method were -29.5 cm/year and -27.0 cm/year, respectively. In addition, we discuss the different subsidence rates where the study area is discriminated into three districts according to distinctive geotechnical characteristics. The significant subsidence rate occurred in the lacustrine sediments with higher compressibility than harder bedrock.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.38 no.6
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• pp.703-711
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• 2001

In this paper, we propose efficient multispectral image compression using variable block size vector quantization (VQ). In wavelet domain, we perform the variable block size VQ to remove intraband redundancy for a reference band image that has the lowest spatial variance and the best correlation with other band. And in wavelet domain, we perform the classified interband prediction to remove interband redundancy for the remaining bands. Then error wavelet coefficients between original image and predicted image are residual variable block size vector quantized to reduce prediction error. Experiments on remotely sensed satellite image show that coding efficiency of the proposed method is better than that of the conventional method.