• Journal of the Semiconductor & Display Technology
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• v.9 no.4
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• pp.57-61
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• 2010

The wavelet transform was adopted as the transform for JPEG2000. However, wavelet has weakness about smoothness along the contours and limited directional information. So we use to other transform, called contourlet transform in compression. Objective quality assessment methods currently used Peak signal to noise Ratio(PSNR). But that is not very well matched to perceived visual quality. So new image quality assessment is required. In this paper, we propose a new method for image compression based on the contourlet transform, which has been recently introduced. In addition we evaluated compression image quality using PSNR and SSIM. Finally contourlet transform has a good result about images with smooth contours and SSIM is good method for image evaluation compared to PSNR.

• Journal of Korea Multimedia Society
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• v.6 no.1
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• pp.58-66
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• 2003

In this paper. an image compression of embedded zerotree structure using multiwavelet filter banks is proposed. Multiwavelet is used DGHM(Donovan, Geronimo, Hardin, and Massopust) scaling functions and wavelet functions of a new method with two channel fillet banks. The important properties of the DGHM multiwavelet are orthogonality and approximation order. The DCHM muitiwavelet using the this paper preserves the approximation order=2 for better energy compaction and perfect reconstruction. Image compression using the preposed DGHM multiwavelet is better PSNR for compression ratio than single Daubechies wavelet(D4), Biorthogoanl wavelet, and GHM(Geronimo, Hardin, and Massopust) multi wavelet.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2002.05a
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• pp.185-188
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• 2002

With improved network system and development of computer technology, a lot of hospitals are equipping PACS that deals with process and transmission of the medical images. Owing to equipment of PACS the problems on transmission and storage of the medical images were treated. The way to solve the problems is to use various image processing techniques and compression methods This paper describes RLC in lossless image compression method, JPEG using DCT in loss image compression applied to medical images as way implementing DICOM standard. Now the medical images were compressed with Wavelet transform method have been taken advantage of image process. And compression rate of each compression methods was analyzed.

• Journal of the Semiconductor & Display Technology
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• v.6 no.3
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• pp.55-59
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• 2007

Wavelet Transform is amenable to efficient algorithms. So wavelet transform was adopted many signal processing and communication applications. For example, the wavelet transform was adopted as the transform for JPEG2000. However, Wavelet has weakness about smoothness along the contours and limited directional information. Hence, recently, some new transforms have been introduced to take advantage of this property. So we use to other transform, called contourlet transform in compression. In this paper, we propose a new method for image compression based on the contourlet transform, which has been recently introduced. Contourlet transform has a good result about images with smooth contours. Moreover, Contourlet is feasible multiresolution and multidirection expansion using non-separable filter bank. This treatise shows a good image representation after compressing using contourlet transform.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39A no.11
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• pp.625-636
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• 2014

In this paper, we propose a new embedded image compression scheme which uses rate-distortion optimized block coding of wavelet coefficients. Unlike to previous works in which set-partition or block-partition is performed according to the magnitude of wavelet coefficients, the proposed scheme achieves rate-distortion optimization by sorting wavelet coefficients or blocks according to their expected rate-distortion slope. At the same time, it performs the optimized block-partition coding using the expected rate-distortion slope of blocks. The proposed scheme also uses various relationship of wavelet coefficients for the entropy coding. Experimental results demonstrate that the proposed image compression scheme provides better overall performance than the existing embedded coding schemes such as SPIHT and EBCOT, in which the PSNR gains of the proposed scheme are about 0.11~1.16dB and -0.18~0.52dB, respectively.

• Journal of the Institute of Electronics Engineers of Korea TE
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• v.39 no.3
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• pp.83-89
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• 2002

A new scheme for image compression based on texture expression in the wavelet transform domain is presented. After taking wavelet transform, using the fact that the high-pass filtered bands has a lower variance than that of the original, a texture expression for the homogeneous polygonal regions can be more efficiently performed in the wavelet transform domain. The estimated texture parameters are transmitted to the receiver and later used for reconstruction after storing in disk. In most cases, the proposed method has yields good results with respects to the compression ratio and reconstructed image quality when our system has compared to conventional SPIHT scheme. 

• Journal of the Institute of Electronics Engineers of Korea TE
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• v.39 no.4
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• pp.423-430
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• 2002

When JPEG, a standard of stopped image compression, is high compressed, the image is severely blocked. Since JPEG performs compression after taking DCT(Discrete Cosine Transform). It has a defect that the quality of image becomes low with aliasing in the case of high compression. Though transformation cipher method can have high compression rate, flame nay happen to quality of image by transformation and reverse transformation. In this paper, we use wavelet transform and fractal theory in order to solve these problems. After we apply these two methods to stopped image, we can get some good results, improvement of speed and compression rate, and elimination of blocking appearance. Besides, we show quality of restoration image is better than established one.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.7B
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• pp.1378-1383
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• 1999

In this paper, an effective variable-block-based image compression technique using wavelet transform is proposed. Since the statistical property of each wavelet subband is different, we apply the adaptive quantization to each wavelet subband. In the proposed algorithm, each subband is divided into non-overlapping variable-sized blocks based on directional properties. In addition, we remove wavelet coefficients which are below a certain threshold value for coding efficiency. To compress the transformed data, the proposed algorithm quantizes the wavelet coefficients using scalar quantizer in LL subband and vector quantizers for other subbands to increase compression ratio. The proposed algorithm shows improvements in compression ratio as well as PSNR compared with the existing block-based compression algorithms. In addition, it does not cause any blocking artifacts in very low bit rates even though it is also a block-based method. The proposed algorithm also has advantage in computational complexity over the existing wavelet-based compression algorithms since it is a block-based algorithm.

• Proceedings of the KIEE Conference
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• 1998.07g
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• pp.2454-2457
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• 1998

In this paper, we interconnected the wavelet transformation and ADPCM to improve the image compression ratio and reduce the loss of information in the reconstructed image. Simulation shows the promising results.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.4C
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• pp.533-540
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• 2004

This paper proposes a new multispectral image data compression algorithm that can efficiently reduce spatial and spectral redundancies by applying classified prediction, a Karhunen-Loeve transform (KLT), and the three-dimensional set partitioning in hierarchical trees (3-D SPIHT) algorithm in the wavelet transform (WT) domain. The classification is performed in the WT domain to exploit the interband classified dependency, while the resulting class information is used for the interband prediction. The residual image data on the prediction errors between the original image data and the predicted image data is decorrelated by a KLT. Finally, the 3-D SPIHT algorithm is used to encode the transformed coefficients listed in a descending order spatially and spectrally as a result of the WT and KLT. Simulation results showed that the reconstructed images after using the proposed algorithm exhibited a better quality and higher compression ratio than those using conventional algorithms.