• Journal of the Korea Society of Computer and Information
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• v.12 no.1 s.45
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• pp.57-65
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• 2007

In the fast block matching algorithm. search patterns of different shapes or sizes and the distribution of motion vectors have a large impact on both the searching speed and the image qualify. In this paper, we propose a new fast block matching algorithm using the flat-hexagon search pattern that ate solved disadvantages of the diamond pattern search algorithm(DS) and the hexagon-based search algorithm(HEXBS). Our proposed algorithm finds mainly the motion vectors that not close to the center of search window using the flat-hexagon search pattern. Through experiments, compared with the DS and HEXBS, the proposed f)at-hexagon search algorithm(FHS) improves about $0.4{\sim}21.3%$ in terms of average number of search point per motion vector estimation and improves about $0.009{\sim}0.531dB$ in terms of PSNR(Peak Signal to Noise Ratio).

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.4
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• pp.714-725
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• 1997

This paper proposes an image compression method using the wavelet transform and bit-plane coding of wavelet coefficients. The hierarchical application of wavelet transform to an image produces one low resoluation(the subband with lowest frequency) image and several high frequency subbands. In the proposed method, the low resolution image is compressed by a lossless method at 8 bits per each coefficient. However, the high frequency subbands are decomposed into 8 bit planes. With an adptive block coding method, the decomposed bit planes are effectively compressed using localized edge information in each bit plane. In addition, the propsoed method can control bit rates by selectively eliminating lessimportant subbands of low significant bit planes. Experimental results show that the proposed scheme has better performance in the peak signal to noise ratio (PSNR) and compression rate than conventional image coding methods using the wavelet transform and vector quantization.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.3
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• pp.425-433
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• 2018

In this paper, we propose a super-resolution reconstruction algorithm for plenoptic images based on the reliability of disparity. The subperture image generated by the Flanoptic camera image is used for disparity estimation and reconstruction of super-resolution image based on TV_L1 algorithm. In particular, the proposed image reconstruction method is effective in the boundary region where disparity may be relatively inaccurate. The determination of reliability of disparity vector is based on the upper, lower, left and right positional relationship of the sub-aperture image. In our method, the unreliable vectors are excluded in reconstruction. The performance of the proposed method was evaluated by comparing to a bicubic interpolation method, a conventional disparity based method and dictionary based method. The experimental results show that the proposed method provides the best performance in terms of PSNR(Peak Signal to noise ratio), SSIM(Structural Similarity).

• Journal of Navigation and Port Research
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• v.35 no.10
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• pp.811-816
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• 2011

In this paper, we analysis to consider the performance of PSPM (Phase Shift Pulse-position Modulation), the one of the low power communication technique, in near-field underwater sound channel by sea trial. PSPM is a QPSK(Quadrature Phase Shift Keying) modulation combined with PPM(Pulse Position Modulation) for low power communication in WBAN(Wireless Body Area Network). It is known that the bandwidth efficiency of PSPM is lower than conventional PSK but the power efficiency increases. In this paper, we will analyze the BER performance of PSPM using data acquired from the sea trials. The BER of QPSK was $6.04{\times}10^{-2}$, PSPM was $3.5{\times}10^{-1}$. Also, PSNR of QPSK was 9.37 dB and in case of PSPM was 9.11 dB.

• Journal of the Institute of Convergence Signal Processing
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• v.2 no.2
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• pp.13-19
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• 2001

The conventional fractal decoding was required a vast amount computational complexity, since every range blocks was implemented to IFS(iterated function system). In order to improve this, it has been suggested that each range block was classified to iterated and non-iterated regions. Non-iterated regions is called data dependency region, and if data dependency region extended, IFS regions are contractive. In this paper, a searched region of the domain is limited to the range regions that is similar with the domain blocks, and the domain region is more overlapped. As a result, data dependency region has maximum region, that is IFS regions can be minimum region. The minimizing method of domain region is defined to minimum domain(MD) which is minimum IFS region. Using the minimizing method of domain region, there is not influence PSNR(peak signal-to-noise ratio). And it can be performed a fast decoding by reducing the computational complexity for IFS in fractal image decoding.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.3
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• pp.62-70
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• 2011

Nowadays image sensor is an essential component in many multimedia devices, and it is covered by a color filter array to filter out specific color components at each pixel. We need a certain algorithm to combine those color components reconstructed a full color image from incomplete color samples output from an image sensor, which is called a demosaicking process. Most existing demosaicking algorithms are developed for ideal image sensors, but they do not work well for the practical cases because of dissimilar characteristics of each sensor. In this paper, we propose a new demosaicking algorithm in which the color filter characteristics are fully utilized to generate a good image. To demonstrate significance of our algorithm, we used a commerically available sensor, CBN385B, which is a sort of Honeycomb-style CFA(Color Filter Array) CCD image sensor. As a performance metric of the algorithm, PSNR(Peak Signal to Noise Ratio) and RGB distribution of the output image are used. We first implemented our algorithm in C-language for simulation on various input images. As a result, we could obtain much enhanced images whose PSNR was improved by 4~8 dB compared to the commonly idealized approaches, and we also could remove the inclined red property which was an unique characteristics of the image sensor(CBN385B).Then we implemented it in hardware to overcome its problem of computational complexity which made it operate slow in software. The hardware was verified on Spartan-3E FPGA(Field Programable Gate Array) to give almost the same performance as software, but in much faster execution time. The total logic gate count is 45K, and it handles 25 image frmaes per second.

• 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.

• Journal of Broadcast Engineering
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• v.20 no.2
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• pp.204-214
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• 2015

Depth map upsampling is an approach to increase the spatial resolution of depth maps obtained from a depth camera. Depth map quality is closely related to 3D perception of stereoscopic image, multi-view image and holography. In general, the performance of upsampled depth map is evaluated by PSNR (Peak Signal to Noise Ratio). On the other hand, time-consuming 3D subjective tests requiring human subjects are carried out for examining the 3D perception as well as visual fatigue for 3D contents. Therefore, if an objective metric is closely correlated with a subjective test, the latter can be replaced by the objective metric. For this, this paper proposes a best metric by investigating the relationship between diverse objective metrics and 3D subjective tests. Diverse reference and no-reference metrics are adopted to evaluate the performance of upsampled depth maps. The subjective test is performed based on DSCQS test. From the utilization and analysis of three kinds of correlations, we validated that SSIM and Edge-PSNR can replace the subjective test.

• Journal of Broadcast Engineering
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• v.16 no.2
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• pp.274-292
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• 2011

This paper proposes an efficient coding method of the depth-map which is different from the natural images. The depth-map are so smooth in both inner parts of the objects and background, but it has sharp edges on the object-boundaries like a cliff. In addition, when a depth-map block is decomposed into bit planes, the characteristic of perfect matching or inverted matching between bit planes often occurs on the object-boundaries. Therefore, the proposed depth-map coding scheme is designed to have the bit-plane unit coding method using the adaptive XOR method for efficiently coding the depth-map images on the object-boundary areas, as well as the conventional DCT-based coding scheme (for example, H.264/AVC) for efficiently coding the inside area images of the objects or the background depth-map images. The experimental results show that the proposed algorithm improves the average bit-rate savings as 11.8 % ~ 20.8% and the average PSNR (Peak Signal-to-Noise Ratio) gains as 0.9 dB ~ 1.5 dB in comparison with the H.264/AVC coding scheme. And the proposed algorithm improves the average bit-rate savings as 7.7 % ~ 12.2 % and the average PSNR gains as 0.5 dB ~ 0.8 dB in comparison with the adaptive block-based depth-map coding scheme. It can be confirmed that the proposed method improves the subjective quality of synthesized image using the decoded depth-map in comparison with the H.264/AVC coding scheme. And the subjective quality of the proposed method was similar to the subjective quality of the adaptive block-based depth-map coding scheme.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.4C
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• pp.533-540
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• 2004

This paper proposes a new multispectral image data compression algorithm that can efficiently reduce spatial and spectral redundancies by applying classified prediction, a Karhunen-Loeve transform (KLT), and the three-dimensional set partitioning in hierarchical trees (3-D SPIHT) algorithm in the wavelet transform (WT) domain. The classification is performed in the WT domain to exploit the interband classified dependency, while the resulting class information is used for the interband prediction. The residual image data on the prediction errors between the original image data and the predicted image data is decorrelated by a KLT. Finally, the 3-D SPIHT algorithm is used to encode the transformed coefficients listed in a descending order spatially and spectrally as a result of the WT and KLT. Simulation results showed that the reconstructed images after using the proposed algorithm exhibited a better quality and higher compression ratio than those using conventional algorithms.