• Title/Summary/Keyword: progressive vector

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Progressive Image Transmission Using Hierarchical Pyramid Structure and Classified Vector Quantizer in DCT Domain (계층적 피라미드 구조와 DCT 영역에서의 분류 벡터 양지기를 이용한 점진적 영상전송)

  • 박섭형;이상욱
    • Journal of the Korean Institute of Telematics and Electronics
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    • v.26 no.8
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    • pp.1227-1237
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    • 1989
  • In this paper, we propose a lossless progressive image transmission scheme using hierarchical pyramid structure and classified vector quantizer in DCT domain. By adopting DCT to the hierarchical pyramid signals, we can reduce the spatial redundance. Moreover, the DCT coefficients can be encoded efficiently by using classified vector quantizer in DCT domain. The classifier is simply based on the variance of a subblock. Also, the mirror set of training set of images can improve the robustness of codebooks. Progressive image transmission can be achieved through following processes: from top to bottom level of planes in a pyramid, and from high to low AC variance class in a plane. Some simulation results with real images show that the proposed coding scheme yields a good performance at below 0.3 bpp and an excellent result at 0.409 bpp. The proposed coding scheme is well suited for lossless progressive image transmission as well as image data compression.

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Tidal and Sub-tidal Current Characteristics in the Kangjin Bay, South Sea, Korea

  • Ro, Young-Jae
    • Ocean Science Journal
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    • v.42 no.1
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    • pp.19-30
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    • 2007
  • This study analyzed the current meter records along with wind records for over 500 days obtained in the Kangjin Bay, South Sea, Korea spanning from March, 2003 to Nov. 2005. Various analyses include descriptive statistics, harmonic analysis of tidal constituents, spectra and coherence, the principal axis, progressive vector diagrams. These analyses can illustrate the response of residual current to the local wind resulting in the net drift with rotational motion. Current speed ranges from -28 to 33 (cm/sec), with standard deviations from 6.5 to 12.9 (cm/sec). The harmonic analyses of the tidal current show the average form number, 0.12 with semi-diurnal type and the rectilinear orientation of the major axis toward northeast. The magnitudes of the semi-major range from 12.7 to 17.7 (cm/sec) for M2 harmonics, while for S2 harmonics, they range from 6.3 to 10.4 (cm/sec), respectively. In the spectral and coherency analysis of residual current and wind, a periodicity of 13.6 (day) is found to be most important in both records and plays an important role in the net drift of residual current. The progressive vector diagrams of residual current and wind show two types of behaviors such as unidirectional drift and rotational motion. It was also found that 3 % rule holds approximately to drive 1 (cm/sec) drift current by 30 (cm/sec) wind speed based on the correlation of the semi-major axis of wind and residual current.

Explicit Matrix Expressions of Progressive Iterative Approximation

  • Chen, Jie;Wang, Guo-Jin
    • International Journal of CAD/CAM
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    • v.13 no.1
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    • pp.1-11
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    • 2013
  • Just by adjusting the control points iteratively, progressive iterative approximation (PIA) presents an intuitive and straightforward scheme such that the resulting limit curve (surface) can interpolate the original data points. In order to obtain more flexibility, adjusting only a subset of the control points, a new method called local progressive iterative approximation (LPIA) has also been proposed. But to this day, there are two problems about PIA and LPIA: (1) Only an approximation process is discussed, but the accurate convergence curves (surfaces) are not given. (2) In order to obtain an interpolating curve (surface) with high accuracy, recursion computations are needed time after time, which result in a large workload. To overcome these limitations, this paper gives an explicit matrix expression of the control points of the limit curve (surface) by the PIA or LPIA method, and proves that the column vector consisting of the control points of the PIA's limit curve (or surface) can be obtained by multiplying the column vector consisting of the original data points on the left by the inverse matrix of the collocation matrix (or the Kronecker product of the collocation matrices in two direction) of the blending basis at the parametric values chosen by the original data points. Analogously, the control points of the LPIA's limit curve (or surface) can also be calculated by one-step. Furthermore, the $G^1$ joining conditions between two adjacent limit curves obtained from two neighboring data points sets are derived. Finally, a simple LPIA method is given to make the given tangential conditions at the endpoints can be satisfied by the limit curve.

Generation of Progressively Sampled DTM using Model Key Points Extracted from Contours in Digital Vector Maps (수치지도 등고선의 Model Key Point 추출과 Progressive Sampling에 의한 수치지형모델 생성)

  • Lee, Sun-Geun;Yom, Jae-Hong;Lim, Sae-Bom;Kim, Kye-Lim;Lee, Dong-Cheon
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.25 no.6_2
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    • pp.645-651
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    • 2007
  • In general, contours in digital vector maps, which represent terrain characteristics and shape, are created by 3D digitizing the same height points using aerial photographs on the analytical or digital plotters with stereoscopic viewing. Hence, it requires lots of task, and subjective decision and experience of the operators. DTMs are generated indirectly by using contours since the national digital maps do not include digital terrain model (DTM) data. In this study, model key points which depict the important information about terrain characteristics were extracted from the contours. Further, determination of the efficient and flexible grid sizes were proposed to generate optimal DTM in terms of both quantitative and qualitative aspects. For this purpose, a progressive sampling technique was implemented, i.e., the smaller grid sizes are assigned for the mountainous areas where have large relief while the larger grid sizes are assigned for the relatively flat areas. In consequence, DTMs with multi-grid for difference areas could be generated instead of DTMs with a fixed grid size. The multi-grid DTMs reduce computations for data processing and provide fast display.

Progressive Image Transmission using LOT/CVQ with HVS Weighting (HVS가중치를 갖는 LOT/CVQ를 이용한 점진적 영상 전송)

  • 황찬식
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.18 no.5
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    • pp.685-694
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    • 1993
  • A progressive image transmission (PIT) scheme based on the classified transform vector quantization (CVQ) technique using the lapped orthogonal transform (LOT) and human visual system (HVS) weighting is proposed in this paper. Conventional block transform coding of images using DCT produces in general undesirable block-artifacts at low bit rates. In this paper, image blocks are transformed using the LOT and classified into four classes based on their structural properties and further divided adaptively into subvectors depending on the LOT coefficient statistics with HVS weighting to improve the reconstructed image quality by adaptive bit allocation. The subvectors are vector quantized and transmitted progressively. Coding tests using computer simulations show that the LOT/CVQ based PIT of images is a effective coding scheme. The results are also compared with those obtained using PIT/DCTVQ. The LOT/CVQ based PIT reduces the block-artifacts significantly.

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Sharing a Large Secret Image Using Meaningful Shadows Based on VQ and Inpainting

  • Wang, Zhi-Hui;Chen, Kuo-Nan;Chang, Chin-Chen;Qin, Chuan
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.9 no.12
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    • pp.5170-5188
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    • 2015
  • This paper proposes a novel progressive secret image-hiding scheme based on the inpainting technique, the vector quantization technique (VQ) and the exploiting modification direction (EMD) technique. The proposed scheme first divides the secret image into non-overlapping blocks and categorizes the blocks into two groups: complex and smooth. The blocks in the complex group are compressed by VQ with PCA sorted codebook to obtain the VQ index table. Instead of embedding the original secret image, the proposed method progressively embeds the VQ index table into the cover images by using the EMD technique. After the receiver recovers the complex parts of the secret image by decoding the VQ index table from the shadow images, the smooth parts can be reconstructed by using the inpainting technique based on the content of the complex parts. The experimental results demonstrate that the proposed scheme not only has the advantage of progressive data hiding, which involves more shadow images joining to recover the secret image so as to produce a higher quality steganography image, but also can achieve high hiding capacity with acceptable recovered image quality.

Wavelet Packet-Based Progressive Image Transmission (Wavelet Packet 기반 점진적 영상 전송)

  • Song, Joon-Ho;Lee, Gi-Hun;Park, Rae-Hong
    • Journal of the Korean Institute of Telematics and Electronics S
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    • v.35S no.8
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    • pp.77-85
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    • 1998
  • This paper proposes progressive image transmission(PIT) methods based on the wavelet packet transform, in which quantizers are optimized at each stage for the given bit rate. Scalar and vector quantizers are used and the performance of each quantizer is compared. After quantization, selected subbands are ordered by their priority for transmission. Subjective quality of the reconsetructed image is improved by human visual system (HVS) weighting.

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Tidal and Sub-tidal Current Characteristics in the Central part of Chunsu Bay, Yellow Sea, Korea during the Summer Season (서해 천수만 중앙부의 하계 조류/비조류 특성)

  • Jung, Kwang Young;Ro, Young Jae;Kim, Baek Jin
    • The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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    • v.18 no.2
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    • pp.53-64
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    • 2013
  • This study analyzed the ADCP records along with wind by KMA and discharge records at Seosan A-, B-district tide embankment by KRC for 33 days obtained in the Chunsu Bay, Yellow Sea, Korea spanning from July 29 to August 30, 2010. Various analyses include descriptive statistics, harmonic analysis of tidal constituents, spectra and coherence, complex correlation, progressive vector diagram and cumulative curves to understand the tidal and sub-tidal current characteristics caused by local wind and discharge effect. Observed current speed ranges from -30 to 40 (cm/sec), with standard deviation from 1.7 (cm/sec) at bottom to 18.7 (cm/sec) at surface. According to the harmonic analysis results, the tidal current direction show NNW-SSE. The magnitudes of semi-major axes range from 9.4 to 14.8 (cm/sec) for M2 harmonic constituent and from 4.4 to 7.0 (cm/sec) for S2, respectively. And the magnitudes of semi-minor axes range from 0.1 to 0.5 (cm/sec) for M2 and from 0.4 to 1.4 (cm/sec) for S2, respectively. In the spectral analysis results in the frequency domain, we found 3~6 significant spectral peaks for band-passed wind and residual current of all depth. These peak periods represent various periodicities ranging from 2 to 8 (days). In the coherency analysis results between band-passed wind and residual current of all depth, several significant coherencies could be resolved in 3~5 periodicities within 2.8 (days). Highest coherency peak occurred at 4.6 (day) with 1.2-day phase lag of discharge to band-passed residual current. The progressive vector of wind and residual current travelled to northward at all layers, and the travel distance at middle layer was greater than surface layer distance. The Northward residual current was caused by a seasonal southern wind, and the density-driven current formed by fresh water input effected southward residual current. The sub-tidal current characteristics is determined by seasonal wind force and fresh water inflow in the Chunsu Bay, Yellow Sea, Korea.

Robust Face Alignment using Progressive AAM (점진적 AAM을 이용한 강인한 얼굴 윤곽 검출)

  • Kim, Dae-Hwan;Kim, Jae-Min;Cho, Seong-Won;Jang, Yong-Suk;Kim, Boo-Gyoun;Chung, Sun-Tae
    • The Journal of the Korea Contents Association
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    • v.7 no.2
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    • pp.11-20
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    • 2007
  • AAM has been successfully applied to face alignment, but its performance is very sensitive to initial values. In this paper, we propose a face alignment method using progressive AAM. The proposed method consists of two stages; modelling and relation derivation stage and fitting stage. Modelling and relation derivation stage first builds two AAM models; the inner face AAM model and the whole face AAM model and then derive the relation matrix between the inner face AAM model parameter vector and the whole face AAM model parameter vector. The fitting stage is processed progressively in two phases. In the first phase, the proposed method finds the feature parameters for the inner facial feature points of a new face, and then in the second phase it localizes the whole facial feature points of the new face using the initial values estimated utilizing the inner feature parameters obtained in the first phase and the relation matrix obtained in the first stage. Through experiments, it is verified that the proposed progressive AAM-based face alignment method is more robust with respect to pose, and face background than the conventional basic AAM-based face alignment.

Image Retrieval Using Multiresoluton Color and Texture Features in Wavelet Transform Domain (웨이브릿 변환 영역의 칼라 및 질감 특징을 이용한 영상검색)

  • Chun Young-Deok;Sung Joong-Ki;Kim Nam-Chul
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.43 no.1 s.307
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    • pp.55-66
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    • 2006
  • We propose a progressive image retrieval method based on an efficient combination of multiresolution color and torture features in wavelet transform domain. As a color feature, color autocorrelogram of the hue and saturation components is chosen. As texture features, BDIP and BVLC moments of the value component are chosen. For the selected features, we obtain multiresolution feature vectors which are extracted from all decomposition levels in wavelet domain. The multiresolution feature vectors of the color and texture features are efficiently combined by the normalization depending on their dimensions and standard deviation vector, respectively, vector components of the features are efficiently quantized in consideration of their storage space, and computational complexity in similarity computation is reduced by using progressive retrieval strategy. Experimental results show that the proposed method yields average $15\%$ better performance in precision vs. recall and average 0.2 in ANMRR than the methods using color histogram color autocorrelogram SCD, CSD, wavelet moments, EHD, BDIP and BVLC moments, and combination of color histogram and wavelet moments, respectively. Specially, the proposed method shows an excellent performance over the other methods in image DBs contained images of various resolutions.