• Journal of the Institute of Electronics Engineers of Korea CI
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• v.37 no.3
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• pp.45-55
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• 2000

In this paper, we proposed the hardware architecture of wavelet transform digital filter for an image processing. Filter bank pyramid algorithm is used for wavelet transform and each fillet is implemented by the FIR filter. For DWT computation, because the memory controller is implemented by hardware, we can efficiently process the multisolution decomposition of the image data only input the parameter. As a result of the image Processing in this paper, 33㏈ PSNR has been obtained on 512$\times$512 B/W image due to 11-bit mantissa processing in FPGA Implementation. And because of using QMF( Quadrature Mirror Filter) properties, it reduces half number of the multiplier needed DWT(Discrete Wavelet Transform) computation so the hardware size is reduced largely. The proposed scheme can increase the efficiency of an image Processing as well as hardware size reduced. The hardware design proposed of DWT fillet bank is synthesized by VHDL coding and then the test board is manufactured, the operating Program and the application Program are implemented using MFC++ and C++ language each other.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.19 no.12
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• pp.2313-2327
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• 1994

As the communication environment evolves, there is an increasing need for multiresolution image coding. To meet this need, the entrophy constratined vector quantizer(ECVQ) for coding of image pyramids by spline wavelet transform is introduced in this paper. This paper proposes a new scheme for image compression taking into account psychovisual feature both in the space and frequency domains : this proposed method involves two steps. First we use spline wavelet transform in order to obtain a set of biorthogonal subclasses of images ; the original image is decomposed at different scale using a pyramidal algorithm architecture. The decomposition is along the vertical and horizontal directions and maintains constant the number of pixels required the image. Second, according to Shannon's rate distortion theory, the wavelet coefficients are vectored quantized using a multi-resolution ECVQ(entropy-constrained vector quantizer) codebook. The simulation results showed that the proposed method could achieve higher quality LENA image improved by about 2.0 dB than that of the ECVQ using other wavelet at 0.5 bpp and, by about 0.5 dB at 1.0 bpp, and reduce the block effect and the edge degradation.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.37 no.1
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• pp.49-58
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• 2000

This paper presents a new color Image coding method which estimates color component Images from luminance image using spectral correlation m wavelet transformed domain More specifically, the wavelet transform is performed to the luminance image(Y), and then, for an efficient quad-tree division to encompass the varying block size, a cost function IS defined using high frequency coefficients generated by wavelet decomposition Next, a scale factor and an offset factor for each the block to minimize the estimation error between luminance image(Y) and R, B Images, are iteratively calculated With respect to the varying block size With associated cost function.

• Journal of KIISE:Software and Applications
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• v.31 no.10
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• pp.1386-1399
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• 2004

This paper presents correlation-based automatic image captioning. Given a training set of annotated images, we want to discover correlations between visual features and textual features, so that we can automatically generate descriptive textual features for a new unseen image. We develop models with multiple design alternatives such as 1) adaptively clustering visual features, 2) weighting visual features and textual features, and 3) reducing dimensionality for noise sup-Pression. We experiment thoroughly on 10 data sets of various content styles from the Corel image database, about 680MB. The major contributions of this work are: (a) we show that careful weighting visual and textual features, as well as clustering visual features adaptively leads to consistent performance improvements, and (b) our proposed methods achieve a relative improvement of up to 45% on annotation accuracy over the state-of-the-art, EM approach.

• Journal of the Korean Chemical Society
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• v.46 no.5
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• pp.437-471
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• 2002

The photosensitivity enhancement of photoresist achieved by the addition of acid amplifiers stems from the autocatalytic decomposition of the acid amplifiers triggered by acidic species generated from a photoacid gen-erator. In this research we synthesized and evaluated 4-hydroxy-4'-p-styrenesulfonyloxy isopropylidene dicyclohex-ane(1), 4,4'-di-p-styrenesulfonyloxy isopropylidene dicyclohexane(2) and 4-p-styrenesulfonyloxy-4'-tosyloxy isopropylidene dicyclohexane(3) as novel acid amplifiers. These acid amplifiers(1-3) showed reasonable thermal stability for resist pro-cessing temperature. As estimated by the sensitivity curve, 1-3 were 2X-12X sensitive than poly(tert-butyl meth-acrylate) film in the presence of a photoacid generator and, therefore, provides practical applicability for photoimaging.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.9
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• pp.1703-1710
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• 2017

This paper propose a 3D point clouds (depth) security technique for digital holographic display service. Image contents encryption is a method to provide only authorized right owners with the original image information by encrypting the entire image or a part of the image. The proposed method detected an edge from a depth and performed quad tree decomposition, and then performed encryption. And encrypts the most significant block among the divided blocks. The encryption effect was evaluated numerically and visually. The experimental results showed that encrypting only 0.43% of the entire data was enough to hide the constants of the original depth. By analyzing the encryption amount and the visual characteristics, we verified a relationship between the threshold for detecting an edge-map. As the threshold for detecting an edge increased, the encryption ratio decreased with respect to the encryption amount.

• The KIPS Transactions:PartB
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• v.12B no.4 s.100
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• pp.421-428
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• 2005

A new method of Semi-fragile image watermarking which ensures the integrity of the contents of digital image is presented. Proposed watermarking scheme embeds watermark in the form of quantization noise on the wavelet transform coefficients in a specific mid frequency subbands selected from a wavelet packet decomposition based on energy distribution of wavelet transform coefficients. By controlling the strength of embedded watermark using HVS (Human Visual System) characteristic, it is imperceptible by a human viewer while robust against non-malicious attack such as compression for storage and/or transmission. When an attack is applied on the original image, it is highly probable that wavelet transform coefficients not only at the exact attack positions but also the neighboring ones are modified. Therefore, proposed authentication method utilizes whether both current coefficient and its neighbors are damaged. together. So it can efficiently detect and accurately localize attacks inflicted on the content of original image. Decision threshold for authentication can be user controlled for different application areas as needed.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.12
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• pp.2714-2726
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• 1997

In this paper, adaptive symbol changes-based medical image compression method is presented. First, the differenctial image domain is obtained using the differentiation rules or obaptive predictors applied to original mdeical image. Also, the algorithm determines the context associated with the differential image from the domain. Then prediction symbols which are thought tobe the most probable differential image values are maintained at a high value through the adaptive symbol changes procedure based on estimates of the symbols with polarity coincidence between the differential image values to be coded under to context and differential image values in the model template. At the coding step, the differential image values are encoded as "predicted" or "non-predicted" by the binary adaptive arithmetic encoder, where a binary decision tree is employed. The simlation results indicate that the prediction hit ratios of differential image values using the proposed algorithm improve the coding gain by 25% and 23% than arithmetic coder with ISO JPEG lossless predictor and arithmetic coder with differentiation rules or adaptive predictors, respectively. It can be used in compression part of medical PACS because the proposed method allows the encoder be directly applied to the full bit-planes medical image without a decomposition of the full bit-plane into a series of binary bit-planes as well as lower complexity of encoder through using an additions when sub-dividing recursively unit intervals.

• Journal of Broadcast Engineering
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• v.1 no.2
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• pp.118-132
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• 1996

This paper proposes a wavelet transform- based image compression method using the energy distribution. The proposed method Involves two steps. First, we use a wavelet transform for the subband decomposition. The original image Is decomposed into one low resolution subimage and three high frequency subimages. Each high frequency subimages have horizontal, vertical, and diagonal directional edges. The wavelet transform is luther applied to these high frequency subimages. Resultant transformed subimages have different energy distributions corresponding to different orientation of the high pass filter. Second, for higer compression ratio and computational effciency, we discard some subimages with small energy. The remaining subimages are encoded using either DPCM or quantization followed by entropy coding. Experimental results show that the proposed coding scheme has better performance in the peak signal to noise ratio(PSNR) and higher compression ratio than conventional image coding method using the wavelet transform followed by the straightforward vector quantization.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.383-388
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• 2005

Depth recovery in robot vision is an essential problem to infer the three dimensional geometry of scenes from a sequence of the two dimensional images. In the past, many studies have been proposed for the depth estimation such as stereopsis, motion parallax and blurring phenomena. Among cues for depth estimation, depth from lens translation is based on shape from motion by using feature points. This approach is derived from the correspondence of feature points detected in images and performs the depth estimation that uses information on the motion of feature points. The approaches using motion vectors suffer from the occlusion or missing part problem, and the image blur is ignored in the feature point detection. This paper presents a novel approach to the defocus technique based depth from lens translation using sequential SVD factorization. Solving such the problems requires modeling of mutual relationship between the light and optics until reaching the image plane. For this mutuality, we first discuss the optical properties of a camera system, because the image blur varies according to camera parameter settings. The camera system accounts for the camera model integrating a thin lens based camera model to explain the light and optical properties and a perspective projection camera model to explain the depth from lens translation. Then, depth from lens translation is proposed to use the feature points detected in edges of the image blur. The feature points contain the depth information derived from an amount of blur of width. The shape and motion can be estimated from the motion of feature points. This method uses the sequential SVD factorization to represent the orthogonal matrices that are singular value decomposition. Some experiments have been performed with a sequence of real and synthetic images comparing the presented method with the depth from lens translation. Experimental results have demonstrated the validity and shown the applicability of the proposed method to the depth estimation.