• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2000.08a
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• pp.313-316
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• 2000

Wavelet transform has specific properties for image coding. The property used at this Paper is clustering of significant coefficients across subband. These coefficients are classified in significant coefficient and insignificant coefficient on a threshold value, and symbolized EZW decreases symbol-position information using zero-trees, but threshold value fall for raising resolution, then coding cost of significant coefficients is expensive. To avoid this fact, this paper uses quad-tree representing coefficient-position information. a magnitude of significant coefficient is represented on matrix used at EZW. the proposed algorithm is hoped for raising a coding cost.

• The KIPS Transactions:PartB
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• v.12B no.7 s.103
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• pp.729-736
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• 2005

In this paper. the proposed method for the digital watermarking is based on the multiresolution wavelet transform. The 1-level Discrete Wavelet Transform(DWT) coefficients of a $2N_{wx}{\times}2N_{wy}$ binary logo image used as a watermarks. The LL band and middle frequency band of the host image that the 3-level DWT has been performed are divided into $N_{wx}{\times}N_{wy}$ size and we use large coefficients at the divided blocks to make threshold. we set the thresholds that completely insert the watermark in each frequency of the host image. The thresholds in each frequency of the host image differ each other. The watermarks where is the same positions are added to the larger coefficients than threshold in the blocks at LL band and middle frequency band in order to prevent the quality deterioration of the host image. The watermarks are inserted in LL band and middle frequency band of the host image. In order to be invisibility of the watermark, the Human Visual System(HVS) is applied to the watermark. We prove the proper embedding method by experiment. We rapidly detect the watermark using this watermarking method. And because the small size watermarks are inserted by HVS, the results confirm the superiority of the proposed method on invisibility and robustness.

• Journal of Broadcast Engineering
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• v.13 no.5
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• pp.732-743
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• 2008

In H.264/AVC, 4$\times$4 block transform is used for intra and inter prediction instead of 8$\times$8 block transform. Using small block size coding, H.264/AVC obtains high temporal prediction efficiency, however, it has limitation in utilizing spatial redundancy. Motivated on these points, we propose a multi-dimensional transform which achieves both the accuracy of temporal prediction as well as effective use of spatial redundancy. From preliminary experiments, the proposed multi-dimensional transform achieves higher energy compaction than 2-D DCT used in H.264. We designed an integer-based transform and quantization coder for multi-dimensional coder. Moreover, several additional methods for multi-dimensional coder are proposed, which are cube forming, scan order, mode decision and updating parameters. The Context-based Adaptive Variable-Length Coding (CAVLC) used in H.264 was employed for the entropy coder. Simulation results show that the performance of the multi-dimensional codec appears similar to that of H.264 in lower bit rates although the rate-distortion curves of the multi-dimensional DCT measured by entropy and the number of non-zero coefficients show remarkably higher performance than those of H.264/AVC. This implies that more efficient entropy coder optimized to the statistics of multi-dimensional DCT coefficients and rate-distortion operation are needed to take full advantage of the multi-dimensional DCT. There remains many issues and future works about multi-dimensional coder to improve coding efficiency over H.264/AVC.

• Journal of Broadcast Engineering
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• v.21 no.3
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• pp.380-390
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• 2016

The field of Image Quality Measure (IQM) is growing rapidly in recent years. In particular, there was a significant progress in No-Reference (NR) IQM methods. In this paper, a general-purpose NR IQM algorithm is proposed based on the statistical characteristics of natural images in shearlet domain. The method utilizes a set of distortion-sensitive features extracted from statistical properties of shearlet coefficients. A complex version of the shearlet transform is employed to take advantage of phase and amplitude features in quality estimation. Furthermore, since shearlet transform can analyze the images at multiple scales, the effect of distortion on across-scale dependencies of shearlet coefficients is explored for feature extraction. For quality prediction, the features are used to train image classification and quality prediction models using a Support Vector Machine (SVM). The experimental results show that the proposed NR IQM is highly correlated with human subjective assessment and outperforms several Full-Reference (FR) and state-of-art NR IQMs.

• Journal of the Korean earth science society
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• v.34 no.1
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• pp.69-80
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• 2013

Terrain data is one of important basic data in various areas of Earth science. Recently, finer DEM data is available, which necessary to develop a method that deals with such huge data efficiently. This study was conducted on the lossless compression of DEM data and efficient partial reconstruction of terrain information from compressed data. In this study, we compressed the wavelet coefficients of DEM, obtained from integer wavelet transform (IWT) by entropy encoding. CDF (Cohen-Daubechies-Feauveau) 3.5 wavelet showed the best compression ratio of about 45.4% and the optimum decomposition level was 3. Results also showed that a small region of terrain could be restored from the inverse wavelet transform with a part of the wavelet coefficients that are related to such region instead of whole reconstruction. We discussed the potential applications of the terrain data compression for precise gravity terrain correction.

• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.169-172
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• 2008

Land-use or land-cover classification of satellite images is one of the important tasks in remote sensing application and many researchers have been tried to enhance classification accuracy. Previous studies show that the classification technique based on wavelet transform is more effective than that of traditional techniques based on original pixel values, especially in complicated imagery. Various wavelets can be used in wavelet transform. Wavelets are used as basis functions in representing other functions, like sinusoidal function in Fourier analysis. In these days, some basis functions such as Haar, Daubechies, Coiflets and Symlets are mainly used in 2D image processing. Selecting adequate wavelet is very important because different results could be obtained according to the type of basis function in classification. However, it is not easy to choose the basis function which is effective to improve classification accuracy. In this study, we computed the wavelet coefficients of satellite image using 10 different basis functions, and then classified test image. After evaluating classification results, we tried to ascertain which basis function is the most effective for image classification. We also tried to see if the optimum basis function is decided by energy parameter before classifying the image using all basis function. The energy parameter of signal is the sum of the squares of wavelet coefficients. The energy parameter is calculated by sub-bands after the wavelet decomposition and the energy parameter of each sub-band can be a favorable feature of texture. The decision of optimum basis function using energy parameter in the wavelet based image classification is expected to be helpful for saving time and improving classification accuracy effectively.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.8C
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• pp.712-719
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• 2007

In this paper, we propose a new, effective, fast motion estimation algorithms using $4{\times}4$ pixels Hadamard transform. The Hadamard transform has the advantage of simplicity because it uses only addition and subtraction. Motion estimation is composed of three stages. First, it should be decided whether to terminate the search early and use a previous motion vector with DC(Direct Current) coefficients. Then the adaptive matching scan order for motion estimation should be determined according to the image complexity using AC(Alternating Current) coefficients. Experimentally, we adapted this algorithms to MVFAST and PMVFAST algorithms, and the proposed algorithms turn out to be very efficient in terms of computational speed while remaining almost the same in terms of PSNR(Peak Signal-to-Noise Ratio) compared to MVFAST and PMVFAST algorithms.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.28 no.3
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• pp.353-359
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• 2010

In this paper, we propose the automatic image-to-image registration of high resolution satellite images using local properties of tie points to improve the registration accuracy. A spatial distance between interest points of reference and sensed images extracted by Scale Invariant Feature Transform(SIFT) is additionally used to extract tie points. Coefficients of affine transform between images are extracted by invariant descriptor based matching, and interest points of sensed image are transformed to the reference coordinate system using these coefficients. The spatial distance between interest points of sensed image which have been transformed to the reference coordinates and interest points of reference image is calculated for secondary matching. The piecewise linear function is applied to the matched tie points for automatic registration of high resolution images. The proposed method can extract spatially well-distributed tie points compared with SIFT based method.

• Journal of Broadcast Engineering
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• v.17 no.1
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• pp.26-36
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• 2012

Since shape of an object in an image carries important information in contents based image retrieval (CBIR), many shape description methods have been proposed to retrieve images using shape information. Among the existing shape based image retrieval methods, the method which employs invariant Zernike moment desciptor (IZMD) showed better performance compared to other methods which employ traditional Zernike moments descriptor in CBIR. In this paper, we propose a new image retrieval method which applies invariant angular radial transform descriptor (IARTD) to obtain higher performance than the method which employs IZMD in CBIR. IARTD is a rotationally invariant feature which consists of magnitudes and alligned phases of angular radial transform coefficients. To produce rotationally invariant phase coefficients, a phase correction scheme is performed while extracting the IARTD. The distance between two IARTDs is defined by combining the differences of the magnitudes and the aligned phases. Through the experiment using MPEG-7 shape dataset, the average bull's eye performance (BEP) of the proposed method is 0.5806 while the average BEPs of the exsiting methods which employ IZMD and traditional ART are 0.4234 and 0.3574, respectively.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.1 no.3
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• pp.97-103
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• 2008

In this paper, $256{\times}256$ input image is classified into a validity block and an edge block of $8{\times}8$ block for image compression. DCT(Discrete Cosine Transform) is executed only for the DC coefficient that is validity coefficients for a validity block. Predict the position where a quantization coefficient becomes 0 for an edge block, I propose new algorithm to execute DCT in the reduced region. Not only this algorithm that I proposed reduces computational complexity of FDCT(Forward DCT) and IDCT(Inverse DCT) and decreases encoding time and decoding time. I let compressibility increase by accomplishing other stability verticality zigzag scan by the block size that was classified for each block at the time of huffman encoding each. In addition, the algorithm that I suggested reduces Run-Length by accomplishing the level verticality zigzag scan that is good for a classified block characteristic and, I offer the compressibility that improved thereby.