• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.586-588
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• 2005

The MSC (Multi Spectral Camera) system is a remote sensing payload to obtain high resolution ground image. This system uses lossy image compression method for &Direct mission& that transmit whole image during one contact. But some image degradation occurred especially at high compression ratio. To reduce this degradation, the MSC uses NUC (Non-uniformity Correction) Unit. This unit correct CCD (Charge Coupled Device)'s high-frequency non-uniformity. So high frequency contents of image can be minimized and whole system SNR can be maximized. But NUC has some disadvantage either. It decreases entire system reliability by adding one electronic system. Adding NUC also led to difficulty of electronic design, assembly and testability. In this paper, the comparison is performed between on-orbit non-uniform correction and on ground correction. by evaluating NUC advantage for the point of view of image quality. Using real MSC parameter and proper model, considerable reference point for the system design came to possible.

• 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 Korean Institute of Information and Commucation Sciences Conference
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• 2002.05a
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• pp.598-601
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• 2002

In this research, robustness of image watermarking mixed Key and Logo scheme was evaluated. A personal ID of a copyrighter was key and watermark was logo image. The standard images of Baboon, Cameraman and Lena were used for experimental images, binary image‘Park’of 32$\times$32 and 64$\times$64 size were used for the watermark image, respectively. for robustness evaluation of the watermark, reconstructive rates of the watermark were obtained from images inserted watermark with image transformation or JPEG lossy compression. The experimental results show that the reconstructive rates of the case of 32$\times$32 watermark was better than the case of the 64$\times$64 watermark; average 5.9%, 13.9%, 6.5%, and 4.2% in the case of scale-down rates, rotational rates, impulse noise power density, and JPEG lossy compression rates, respectively.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.4 no.3
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• pp.263-269
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• 2003

This paper focuses on lossy medical image compression methods for medical images that operate on three-dimensional(3D) irreversible integer wavelet transform. We offer an application of the Set Partitioning in Hierarchical Trees(SPIHT) algorithm〔l-3〕to medical images, using a 3-D wavelet decomposition and a 3-D spatial dependence tree. The wavelet decomposition is accomplished with integer wavelet filters implemented with the lifting method, where careful scaling and truncations keep the integer precision small and the transform unitary. As the compression rate increases, the boundaries between adjacent coding units become increasingly visible. Unlike video, the volume image is examined under static condition, and must not exhibit such boundary artifacts. In order to eliminate them, we utilize overlapping at axial boundaries between adjacent coding units. We have tested our encoder on medical images using different integer filters. Results show that our algorithm with certain filters performs as well. The improvement is visibly manifested as fewer ringing artifacts and noticeably better reconstruction of low contrast.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.3
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• pp.77-83
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• 2015

Block Truncation Coding, or BTC, is a type of lossy image compression technique for grayscale images. It divides the original images into blocks and then reduces the number of grey levels in each block to compute the mean and standard deviation. BTC has also been adapted to video compression. Another variation of BTC is Absolute Moment Block Truncation Coding. AMBTC is computationally simpler than BTC. In this paper, we proposed new image compression method based on BTC, which is applied patterns to improve compression rate and image quality. This method make two codebooks to extract 36 and 64 patterns from the highest frequency patterns in BTC. When you are compressing an image, you compare many block patterns to that of codebook and use to compress indexes of identical patterns. We experiment our proposed scheme with 36 patterns and the experimental results showed the compression rate of 1.37 bpp. In this paper, our proposed scheme showed higher compression rate rather than that of BTC. In experiment, we used standard images for the performance evaluation.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2003.11a
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• pp.61-64
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• 2003

무손실 이미지 압축은 (Lossless Image Compression)은 손실이미지 압축(Lossy Image Compression)에 비해, 압축률(compression ratio)은 떨어지지만, 반면 원이미지와 복원이미지가 완전히 일치하므로, 원인이미지의 품질을 그대로 유지학 수 있다. 따라서, 이미지의 품질(Quality)과 압축효율(compression ratio)은 서로 상반된 관계에 있으며, 지금도 좀 더 놀은 압축효과를 얻으려는 여러 무손실 압축 방법이 발표되고 있다. 무손실 이미지 압축은 이미지의 정확성과 정밀성이 요구되는, 의료영양분야에서 가장 널리 쓰이고 있으며, 그밖에, 원본이미지를 기본으로 다른 이미지프로세싱이 필요한 경우, 압축 복원을 반복적으로 수행할 필요가 있을 때, 기타 사진 예술분야, 원격 영상 등 정밀성이 요구되는 분양에서 쓰이고 있다. [7]. 무손실 이미지 압축의 가장 대표적인 CALIC[3]과 JPEG_LS[2]를 들 수 있다. CALIC은 비교적 높은 압축률을 나타내지만, 3-PASS의 과정을 거치는 복잡도가 지적되고 있다. 반면 JPEG-LS는 압축률은 CALIC에 미치지 못하지만 빠른 코딩/디코딩 속도를 보인다. 본 논문에서는 여거 가지의 예측 모드를 두어, 블록단위별로 주변 CONTEXT에 따라, 최상의 예측 모드를 판단하여, 이를 적용, 픽셀의 여러 값을 최소화하였다. 그 후 적응산술 부호기(Adaptive arithmetc coder)를 이용하여, 인코딩을 하였다. 이때 최대 에러값은 64를 넘지 않게 했으며, 또한 8*8블록별로 에러의 최대값을 측정하여 그 값을 $0\~7$까지의 8개의 대표값으로 양자화하는 방법을 통하여 그에 따라 8개의 보호화 심볼 모델중 알맞은 모델에 적용하였다. 이를 통해, 그 소화값의 확률 구간을 대폭 넓힘으로써, 에러 이미지가 가지고 있는 엔트로피에 좀 근접하게 코딩을 할 수 있게 되었다. 이 방법은 실제로 Arithmetic Coder를 이용하는 다른 압축 방법에 그리고 적용할 수 있다. 실험 결과 압축효율은 JPEG-LS보다 약 $5\%$의 압축 성능 개선이 있었으며, CALIC과는 대등한 압축률을 보이며, 부호화/복호화 속도는 CALIC보다 우수한 것으로 나타났다.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.40 no.1
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• pp.45-51
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• 2003

JPEG200, a new international standard for still image compression based on wavelet and bit-plane coding techniques, is developed. In this paper, we design the DWT(Discrete Wavelet Transform) and quantizer for JPEG2000 CODEC. DWT handles both lossy and lossless compression using the same transform-based framework: The Daubechies 9/7 and 5/3 transforms, and quantizer is implemented as SQ(Scalar Quantization). The architecture of the proposed DWT and SQ are synthesized and verified using Xilinx FPGA technology. It operates up to 30MHz, and executes algorithms of wavelet transform and quantization for VGA 10 frame per second.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.7-12
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• 2009

In JPEG2000, the Cohen-Daubechies-Feauveau (CDF) 9/7-tap wavelet filter adopted in lossy compression is implemented by the lifting scheme or by the convolution scheme while the LeGall 5/3-tap wavelet filter adopted in lossless compression is implemented just by the lifting scheme. However, these filters are not optimal in terms of Peak Signal-to-Noise Ratio (PSNR) values, and irrational coefficients of wavelet filters are complicated. In this paper, we proposed a method to optimize image quality based on wavelet filter design and on wavelet decomposition. First, we propose a design of wavelet filters by selecting the most appropriate rational coefficients of wavelet filters. These filters are shown to have better performance than previous wavelet ones. Then, we choose the most appropriate wavelet decomposition to get the optimal PSNR values of images.

• Proceedings of the Korean Information Science Society Conference
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• 2002.10d
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• pp.454-456
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• 2002

압축 방법에는 크게 손실(lossy)압축과 무손실(lossless)압축으로 나눌 수 있다. 그 중 프랙탈 이미지 압축은 lossy 압축의 한가지 방법으로서 개별적인 화소들에 대한 자료를 저장하기보다는, 영상 생성을 위한 명령이나 방식을 저장하는 방법이다. 특히 이미지의 내에 자기유사성(self-similarity)과 중복성(Redundancy)을 이용하여 관련성을 발견하고 수학적인 공식으로 표현하려는 방식이다. 그러나 이미지를 Domain과 Range로 블록화 한 후 유사한 이미지를 찾아내는 데 걸리는 시간이 상당히 길다. 여기에서는 Domain과 Range의 외곽선의 기울기의 부호를 이용하여 블록을 16가지로 클래스화 하여서, 전체의 Domain 블록을 탐색하는 데 걸리는 시간을 줄이고자 하였다. 전체 탐색을 하는 경우보다 10배 이상의 속도향상을 보였고, 이미지에 따라서는 PSNR 값의 손실도 없음을 보였다.

• Proceedings of the Korean Society Of Semiconductor Equipment Technology
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• 2004.05a
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• pp.217-222
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• 2004

This paper focuses on lossy medical image compression methods for medical images that operate on two-dimensional(2D) integer wavelet transform. We offer an application of the Set Partitioning in Hierarchical Trees(SPIHT) algorithm to medical images, using a 2D wavelet decomposition and a 2D spatial dependence tree. The wavelet decomposition is accomplished with integer wavelet filters implemented with the lifting method, where careful scaling and truncations keep the integer precision small and the transform unitary. We have tested our encoder on medical images using different integer filters. Results show that our algorithm with certain filters performs as well and is sometimes better lossy coding using 2D integer wavelet transforms on medical images.