• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.4B
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• pp.715-724
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• 2000

This Paper presents 3-D subband filter banks which are effective for progressive and lossless compression of volumetric images. For such a purpose, ORT(Overlapping Rounding Transform), applied so far to 1-D losslesssubband filter banks, is now used to implement two types of 3-D lossless subband filter banks: separable andnon-separable types. Separable fiter banks are implemented form applying 1-D lossless filter banks consecutively.Non-separable later banks are developed by expanding the 1-D ORT into 3-D one. In particular, the proposed ORT based 3-D non-separable filter banks generalizes the 3-D HINT(Hierarchical INTerpolation) algorithm.Through the experiment comparisons on various volumetric medical images, we prove that the proposedseparablefnon-separable filter banks perform better, in terms of compression ratio (first order entropy), than theother lossless compression techniques such as block based transform and conventional 3-D HINT.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.11
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• pp.2068-2086
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• 2011

Based on the quincunx sub-sampling grid, the New Interleaved Hierarchical INTerpolation (NIHINT) method is recognized as a superior pyramid data structure for the lossless and progressive coding of natural images. In this paper, we propose a new image interpolation algorithm, Edge Adaptive Hierarchical INTerpolation (EAHINT), for a further reduction in the entropy of interpolation errors. We compute the local variance of the causal context to model the strength of a local edge around a target pixel and then apply three statistical decision rules to classify the local edge into a strong edge, a weak edge, or a medium edge. According to these local edge types, we apply an interpolation method to the target pixel using a one-directional interpolator for a strong edge, a multi-directional adaptive weighting interpolator for a medium edge, or a non-directional static weighting linear interpolator for a weak edge. Experimental results show that the proposed algorithm achieves a better compression bit rate than the NIHINT method for lossless image coding. It is shown that the compression bit rate is much better for images that are rich in directional edges and textures. Our algorithm also shows better rate-distortion performance and visual quality for progressive image transmission.

• Journal of Broadcast Engineering
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• v.13 no.1
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• pp.99-108
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• 2008

This raper analyzes the effect of visually lossless image compression for efficient distribution of digital cinema. Currently, distribution of digital cinema is carried out based on JPEG 2000 standard that has been selected by DCI. We first summarize characteristics of JPEG 2000, and then define the concept of visually lossless coding that plays an important role in digital cinema distribution. We provide a test for JPEG 2000 compression performance according to DCI specification for visually lossless. Based on the experiment, the result satisfies high quality for cinema distribution.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.7C
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• pp.671-680
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• 2009

The diagnostic medical images(CT, MRI) in PACS require large storage and long transmission time. A simple and cheap way of overcoming these limitations is to increase the compression ratio. However, this requires a clinical validation for accurate diagnostic applications. The aim of this paper is to improve the compression efficiency of lossless JPEG2000 for diagnostic CT images by performing a visual-Iossless threshold filtering in high frequency subband. A proposed method, based on 5/3 reversible DWT, provides different subband-threshold values according to the compression ratio and gives the high subjective quality to reconstructed diagnostic CT images.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.6
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• pp.1273-1278
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• 2012

In this paper, we introduce modified integer transforms for lossless image compression and evaluate their performances for two-dimensional transforms. The two-dimensional extensions of the modified integer transforms show different performances in terms of coding efficiency and computational complexity. Thus, we measure performances for two-dimensional separable transforms and a two-dimensional non-separable transform. The separable modified integer transform used in H.264, the modified integer transform using the lifting scheme, and the non-separable transform in JPEG XR are evaluated in this paper. Also, experiments and their results are given. The experimental results indicate that the modified integer transform using the lifting scheme shows the best performance in terms of compression efficiency.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.4
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• pp.736-739
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• 2009

In this paper, an efficient lossless compression algorithm using motion adaptation is proposed. It is divided into two parts: a motion adaptation based nonlinear predictor part and a residual data coding part. The proposed nonlinear predictor can reduce prediction error by learning from its past prediction errors using motion adaption. The predictor decides the proper selection of the intra and inter prediction values according to the past prediction error. The reduced error is coded by existing context adaptive coding method. Experimental results show that the proposed algorithm has the higher compression ratio than context modeling methods, such as FELICS, CALIC, and JPEG-LS.

• 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).

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.921-922
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• 2008

In this paper, we propose a lossless compression algorithm using adaptive DPCM(Differential Pulse Coded Modulation) for enhancing the compression ratio. To improve the compression efficiency, various DPCM modification algorithms have been proposed. Proposed algorithm presents 16 DPCM methods and adaptively selects the DPCM method for each block. The experimental results show that proposed DPCM algorithm has better performance on compression ratio than JPEG standard.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.1
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• pp.142-148
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• 2003

We compress medical images in order to solve problems both of request of storage mediums and of a low network speed. In this paper, integration compression environment has been developed for unity of various compression methods. Various compression methods that are implemented by integration compression environment, RLC, Lossless JPEG, and JPEG, comply with the DICOM 3.0. A compression method using DWT is implemented at it. And a unit method of Lossless compression method and lossy compression method is designed to improve images quality and to progress compression ratio. Diverse medical images can be compressed by each compression method. And integration compression environment is operated together database so that information of medical images is administered.

• International Journal of Computer Science & Network Security
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• v.21 no.8
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• pp.196-202
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• 2021

DNA sequencing provides fundamental data in genomics, bioinformatics, biology and many other research areas. With the emergent evolution in DNA sequencing technology, a massive amount of genomic data is produced every day, mainly DNA sequences, craving for more storage and bandwidth. Unfortunately, managing, analyzing and specifically storing these large amounts of data become a major scientific challenge for bioinformatics. Those large volumes of data also require a fast transmission, effective storage, superior functionality and provision of quick access to any record. Data storage costs have a considerable proportion of total cost in the formation and analysis of DNA sequences. In particular, there is a need of highly control of disk storage capacity of DNA sequences but the standard compression techniques unsuccessful to compress these sequences. Several specialized techniques were introduced for this purpose. Therefore, to overcome all these above challenges, lossless compression techniques have become necessary. In this paper, it is described a new DNA compression mechanism of pattern matching extended Compression algorithm that read the input sequence as segments and find the matching pattern and store it in a permanent or temporary table based on number of bases. The remaining unmatched sequence is been converted into the binary form and then it is been grouped into binary bits i.e. of seven bits and gain these bits are been converted into an ASCII form. Finally, the proposed algorithm dynamically calculates the compression ratio. Thus the results show that pattern matching extended Compression algorithm outperforms cutting-edge compressors and proves its efficiency in terms of compression ratio regardless of the file size of the data.