• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1999.06a
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• pp.97.1-102
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• 1999

This paper porposes and efficient coding scheme for remote medical communication systems, or“telemedicine systems”. These systems require a technique which is able to transfer large volume of data such as X-ray images effectively. We have already developed a hierarchical image coding and transmission scheme (HITS), which achieves an efficient transmission of medical images simply[1]. In this paper, a new coding scheme for HITS is proposed, which used hierarchical context modeling for the purpose of improving the coding efficiency. The hierarchical context modeling divides wavelet coefficients into several sets by the value of a correspondent coefficient in their higher class, or“a parent”, optimizes a Golomb-Rice (GR) code parameter in each set, and then encodes the coefficients with the parameter. Computer simulation shows that the proposed scheme is effective with simple implementation. This is due to fact that a wavelet coefficient has dependence on its parent. As a result, high speed data transmission is achieved even if the telemedicine system consists of simple personal computers.

• Korean Journal of Remote Sensing
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• v.22 no.1
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• pp.49-61
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• 2006

The lifting scheme has been found to be a flexible method for constructing scalar wavelets with desirable properties. In this paper, it is extended to the UDAR data compression. A newly developed data compression approach to approximate the UDAR surface with a series of non-overlapping triangles has been presented. Generally a Triangulated Irregular Networks (TIN) are the most common form of digital surface model that consists of elevation values with x, y coordinates that make up triangles. But over the years the TIN data representation has become an important research topic for many researchers due its large data size. Compression of TIN is needed for efficient management of large data and good surface visualization. This approach covers following steps: First, by using a Delaunay triangulation, an efficient algorithm is developed to generate TIN, which forms the terrain from an arbitrary set of data. A new interpolation wavelet filter for TIN has been applied in two steps, namely splitting and elevation. In the splitting step, a triangle has been divided into several sub-triangles and the elevation step has been used to 'modify' the point values (point coordinates for geometry) after the splitting. Then, this data set is compressed at the desired locations by using second generation wavelets. The quality of geographical surface representation after using proposed technique is compared with the original UDAR data. The results show that this method can be used for significant reduction of data set.

• The Journal of the Acoustical Society of Korea
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• v.20 no.8
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• pp.24-30
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• 2001

This article is concerned with automatic segmentation for Korean speech signals. All kinds of transition cases of phonetic units are classified into 3 types and different strategies for each type are applied. The type 1 is the discrimination of silence, voiced-speech and unvoiced-speech. The histogram analysis of each indicators which consists of wavelet coefficients and SVF (Spectral Variation Function) in wavelet coefficients are used for type 1 segmentation. The type 2 is the discrimination of adjacent vowels. The vowel transition cases can be characterized by spectrogram. Given phonetic transcription and transition pattern spectrogram, the speech signal, having consecutive vowels, are automatically segmented by the template matching. The type 3 is the discrimination of vowel and voiced-consonants. The smoothed short-time RMS energy of Wavelet low pass component and SVF in cepstral coefficients are adopted for type 3 segmentation. The experiment is performed for 342 words utterance set. The speech data are gathered from 6 speakers. The result shows the validity of the method.

• Journal of Broadcast Engineering
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• v.4 no.2
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• pp.144-154
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• 1999

The binomial sequences are family of orthogonal sequences that can be generated with remarkable simplicity-no multiplications are necessary. This paper introduces a class of non-recursive multidimensional filters for frequency-selective image processing without multiplication operations. The magnitude responses are narrow-band. approximately gaussian-shaped with center frequencies which can be positioned to yield low-pass. band-pass. or high-pass filtering. Algorithms for the efficient implementation of these filters in software or in hardware are described. Also. we show that the binomial QMFs are the maximally flat magnitude square Perfect Reconstruction paraunitary filters with good compression capability and these are shown to be wavelet filters as well. In wavelet transform the original image is decomposed at different scales using a pyramidal algorithm architecture. The decomposition is along the vertical and horizontal direction and maintains constant the number of pixels required to describe the images. An efficient perfect reconstruction binomial QMF-Wavelet signal decomposition structure is proposed. The technique provides a set of filter solutions with very good amplitude responses and band split. The proposed binomial QMF-filter structure is efficient, simple to implement on VLSl. and suitable for multi-resolution signal decomposition and coding applications.

• Journal of the Korean Society of Radiology
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• v.17 no.5
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• pp.717-723
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• 2023

Liver disease is highly associated with death, and other abdominal diseases are also important causes affecting a person's lifespan, and a CT scan is essential when treating abdominal diseases. High radiation exposure is essential to create images that are good for reading, but managing the patient's radiation exposure is also essential. In this study, a post-processing wavelet algorithm was proposed to improve the image quality of abdominal CT images. Wavelets have the disadvantage of having to set a threshold value depending on the type of input image. Therefore, we experimentally proposed the threshold value of the wavelet and evaluated whether the image quality was effective. As a result of the experiment, the optimal threshold value for abdominal CT images was calculated to be 50. In the case of image 1, noise was improved by 49% and in the case of image 2, by 29%, and the contrast also increased. if the results of this study are applied for post-processing after abdominal CT, image quality can be improved and it will be helpful in disease diagnosis.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.39 no.5
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• pp.486-493
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• 2002

In this paper, we proposed the effective multispectral image compression method using CIBP(classified interband bidrectional prediction) and extended SPIHT(set partition in hierarchical trees) in wavelet domain. We determine separately feature bands that have the highest correlation with other bands in the visible range and in the infrared range of wavelengths. Feature bands are coded to remove the spatial redundancy with SPIHT in the wavelet domain. Prediction bands that have high correlation with feature bands are wavelet transformed and they are classified into one of three classes considering reflection characteristics of the baseband. For Prediction bands, CIBP is performed to reduce the spectral redundancy. for the difference bands between prediction bands and the predicted bands, They are ordered to upgrade the compression efficiency of extended SPIHT with the largest error magnitude. The arranged bands are coded to compensate the prediction error with extended SPIHT. Experiments are carried out on the multispectral images. The results show that the proposed method reconstructs higher quality images than images reconstructed by the conventional methods at the same bit rate.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.38 no.6
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• pp.93-105
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• 2001

In the lossless step of Lattice Vector Quantization(LVQ), the lattice codewords produced at quantization step are enumerated into radius sequence and index sequence. The radius sequence is run-length coded and then entropy coded, and the index sequence is represented by fixed length binary bits. As bit rate increases, the index bit linearly increases and deteriorates the coding performances. To reduce the index bits across the wide range of bit rates, we developed a novel lattice enumeration algorithm adopting the set partitioning method. The proposed enumeration method shifts down large index values to smaller ones and so reduces the index bits. When the proposed lossless coding scheme is applied to a wavelet based image coding, the proposed scheme achieves more than 10% at bit rates higher than 0.3 bits/pixel over the conventional lossless coding method, and yields more improvement as bit rate becomes higher.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.5
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• pp.1025-1030
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• 2005

With the increasing use of multimedia technologies, image compression requires higher performance as well as new functionality. Specially, in the specific area of still image encoding, a new standard, JPEG2000 was developed. This paper proposed Set Partitioning Sorting Algorithm that uses a method to optimized selection of threshold from feature of wavelet transform coefficients and to removes sign bit in LL area on JPEG2000. Experimental results show the proposed algorithm achieves more improved bit rate.

• Proceedings of the Korean Information Science Society Conference
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• 2002.10d
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• pp.547-549
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• 2002

본 논문에서는 웨이블릿(wavelet) 변환된 영상의 압축 방법으로 사용되는 SPIHT(Set Partitioning In Hierarchical Trees)을 이용하여 워터마크를 삽입하는 방법을 제안하였다. 기존의 특정 대역에만 워터마크를 삽입하는 방법은 화질열화와 압축의 두 가지 문제점을 동시에 해결할 수 없었다. 제안된 방법은 웨이블릿 변환된 영상의 계수 값이 동일한 방향을 갖는 부대역 간에 상관관계를 갖는 점을 이용하여 특정 대역이 아닌 중요 계수에만 워터마크를 삽입하므로써 강인성과 비 가시성이 증가되도록 하였다. 워터마크의 추출은 워터마크된 영상과 PN(Pseudo Noise)코드와의 계수 차를 이용하였으며, 워터마크가 삽입된 영상의 인증을 위해 통계학적인 접근 방법을 사용하였다. 실험을 통하여 워터마크가 삽입된 영상에 대해 손실 압축, 잡음, 크로핑, 리사이즈, 콜루션의 공격을 가한 결과 평균 유사도 값이 0.987의 높은 추출율을 보여 강인성을 입증하였다.

• Journal of Korea Society of Digital Industry and Information Management
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• v.16 no.1
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• pp.55-65
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• 2020

With the development of display hardware, image interpolation techniques have been used in various fields such as image zooming and medical imaging. Traditional image interpolation methods, such as bi-linear interpolation, bi-cubic interpolation and edge direction-based interpolation, perform interpolation in the spatial domain. Recently, interpolation techniques in the discrete cosine transform or wavelet domain are also proposed. Using these various existing interpolation methods and machine learning, we propose decision tree classification-based image interpolation methods. In other words, this paper is about the method of adaptively applying various existing interpolation methods, not the interpolation method itself. To obtain the decision model, we used Weka's J48 library with the C4.5 decision tree algorithm. The proposed method first constructs attribute set and select classes that means interpolation methods for classification model. And after training, interpolation is performed using different interpolation methods according to attributes characteristics. Simulation results show that the proposed method yields reasonable performance.