• Korean Journal of Remote Sensing
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• v.23 no.5
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• pp.431-437
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• 2007

Multi-Spectral Camera(MSC) on the KOMPSAT-2 satellite was developed and launched as a main payload to provide 1m of GSD(Ground Sampling Distance) for one(1) channel panchromatic imaging and 4m of GSD for four(4) channel multi-spectral imaging at 685km altitude covering l5km of swath width. Since the compression on MSC image chain was required to overcome the mismatch between input data rate and output date rate JPEG-like method was selected and analyzed to check the influence on the performance. In normal operation the MSC data is being acquired and transmitted with lossy compression ratio to cover whole image channel and full swath width in real-time. In the other hand the MSC performance have carefully been handled to avoid or minimize any degradation so that it was analyzed and restored in KGS(KOMPSAT Ground Station) during LEOP(Launch and Early Operation Phase). While KOMPSAT-2 had been developed, new compression method based upon wavelet for space application was introduced and available for next satellite. The study on improvement of image chain including new compression method is asked for next KOMPSAT which requires better GSD and larger swath width In this paper, satellite image chain which consists of on-board image chain and on-ground image chain including general MSC description is briefly described. The performance influences on the image chain between two on-board compression methods which are or will be used for KOMPSAT are analyzed. The differences on performance between two methods are compared and the better solution for the performance improvement of image chain on KOMPSAT is suggested.

• Proceedings of the KIEE Conference
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• 1987.07b
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• pp.1390-1393
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• 1987

This paper describes the image data compression based on the image decomposition. We reduced the processing time using the segmentation based on the distribution of grey level, and obtained high compression rate using the Huffman run-length coding for the segmented image, and the 2-Dimensional least square curve fitting and the shift coder for each region.

• Proceedings of the IEEK Conference
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• 1999.06a
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• pp.623-626
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• 1999

As the information society is advanced, the needs for mass information storage and retrieval grows. Digital image information is stored in retrieval systems, broadcasting in television transmission and exchanged over several kinds of telecommunication media. A major problem is that digital images are represented with large amount of data. The useful feature of image compression is that transmitting rapidly a lot of data in less time. Therefore we proposed a parallel Fractal trans-formation unit in Fractal Image compression system.

• Proceedings of the KOSOMBE Conference
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• v.1995 no.11
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• pp.113-116
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• 1995

Medical image compression using the wavelet transform has been tried. Due to the flexibility in representing nonstationary image signal in both time and frequency domains and its ability to adapt human visual characteristics, wavelet transform has unique advantage in images compression. In the proposed wavelet compression original image is decomposed into multi-scale bands. Different scale factors are employed in the quantization of wavelet decomposed images in different bands. For the lowest band, a predictor is designed and error signal is entropy coded. For high scale bands, runlength coding for toro run is used with Huffman coding. From simulation with magnetic resonance images($256\times256$ size, 256 graylevels) the proposed algorithm is superior to the JPEG by more than 2.5 dB in near lossless compression (CR = 8 - 10).

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.49 no.3
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• pp.30-36
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• 2012

block truncation coding(BTC) image compression is known as a simple and efficient technology for image compression algorithm. In this paper, we propose RMC-BTC algorithm(RMC : reduction method chrominace data) for color image compression. To compress chrominace data, in every BTC block, the RMC-BTC coding employs chrominace data expressed with average of chrominace data and using method of luminance data bit-map to represented chrominance data bit-map. Experimental results shows efficiency of proposed algorithm, as compared with PSNR and compression ratio of the conventional BTC method.

• Journal of Broadcast Engineering
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• v.26 no.6
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• pp.738-747
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• 2021

Today, with the improvement of deep learning technology, computer vision areas such as image classification, object detection, object segmentation, and object tracking have shown remarkable improvements. Various applications such as intelligent surveillance, robots, Internet of Things, and autonomous vehicles in combination with deep learning technology are being applied to actual industries. Accordingly, the requirement of an efficient compression method for video data is necessary for machine consumption as well as for human consumption. In this paper, we propose an object-based compression of thermal infrared images for machine vision. The input image is divided into object and background parts based on the object detection results to achieve efficient image compression and high neural network performance. The separated images are encoded in different compression ratios. The experimental result shows that the proposed method has superior compression efficiency with a maximum BD-rate value of -19.83% to the whole image compression done with VVC.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1098-1101
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• 2004

The ordinary stereo image of an object consists of data of left and right views. Therefore, the left and right image pairs have to be transmitted simultaneously in order to display 3-dimentional video at the remote site. However, due to the twice data in comparing with a monoscopic image of the same object, it needs to be compressed for fast transmission and resource saving. Hence, it needs an effective coding algorithm for compressing stereo image. It was found previously that compressing left and right frames independently will achieve the compression ratio lower than compressing by utilizing the spatial redundancy between both frames. Therefore, in this paper, we study the stereo image compression technique based on the multiresolution wavelet transform using varied disparity-block size for estimation and compensation. The size of disparity-block in the stereo pair subbands are scaling on a coarse-to-fine wavelet coefficients strategy. Finally, the reference left image and residual right image after disparity estimation and compensation are coded by using SPIHT coding. The considered method demonstrates good performance in both PSNR measures and visual quality for stereo image.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.4
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• pp.29-37
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• 2014

Since multi-view video exists a number of camera color image and depth image, it has a huge of data. Thus, a new compression technique is indispensable for reducing this data. Recently, the effective compression encoding technique for multi-view video that used in layered depth image concepts is a remarkable. This method uses several view point of depth information and warping function, synthesizes multi-view color and depth image, becomes one data structure. In this paper we use actual distance for solving overlap in layered depth image that reduce required data for reconstructing in color-based transform. In experimental results, we confirmed high compression performance and good quality of reconstructed image.

• Journal of Korea Society of Industrial Information Systems
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• v.20 no.5
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• pp.53-60
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• 2015

In this paper, the DCT based lossless image compression system which selects a limited number of DCT coefficients is proposed for the Lenna, Camerman, and Baboon image. The number of DCT coefficients to obtain a suitable image quality for the reconstructed image is computed by simulation. The image size of $256{\times}256$ are used in the experiment. The PSNR values for the reconstructed image by selecting limited number of DCT coefficients are found. It is shown that the minimun number of the coefficients for Lenna, Cameramen Baby and Babbo image to obtain PSNR=30 are N=16, 32, 37, 55, respectively. The result can provide the guideline of the importance of the DCT coefficient toward the compression for the tested image of the Lena, Cameraman, and Baboon.

• Journal of Korea Multimedia Society
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• v.3 no.1
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• pp.53-62
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• 2000

Digital watermarking has been considered as an important technique to protect the copyright of digital content. It is essential that a watermark embedded in a still or moving image resists against various attacks ranging from compression, filtering to cropping. In particular, as JPEG is a dominant still image compression standard for Internet applications, digital watermarking methods that are robust against the JPEG compression are especially required. Most digital watermarking methods proposed so far work by modulating pixels/coefficients without considering the quality level of JPEG, which renders watermarks readily removable. In this paper, we proposed a new digital watermarking method as follows. For providing the robustness against JPEG, the quality level of JPEG is used as parameter on watermarking so as to compute the loss of image caused by JPEG compression and we compute the difference of an original image resulted from JPEG compression. Also in proposed method, we compute the visual components that are derived from the information of edge within image and consideration of brightness discrimination which is one of human visual system's properties. Thus, we proposed new watermarking scheme that after constructing a watermark by considering the loss of image resulted from JPEG compression and visual components derived from the human visual system, the watermark is embedded into the image.