• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.11C
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• pp.925-931
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• 2008

In video coding standard H.264/AVC, variable block size mode algorithm improves compression efficiency but has need of a large amount of computation for various block modes and mode decision. Meanwhile, decided inter block modes depend on the complexity of a block image, and then the more complex a macroblock is, the smaller its block size is. This paper proposes fast inter block mode decision algorithm. It limits valid block modes to the block modes with a great chance for decision using the image complexity and carries out motion estimation rate-distortion optimization with only the valid block modes. In addition to that, it applies fast motion estimation PDE to the valid block modes with only the $16{\times}16$ block mode. The reference software JM 9.5 was executed to estimate the proposed algorithm's performance. The simulation results showed that the proposed algorithm could save about 24.12% of the averaged motion estimation time while keeping the image quality and the bit rate to be -0.02dB and -0.12% on the average, respectively.

• Journal of Broadcast Engineering
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• v.17 no.4
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• pp.634-639
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• 2012

In this paper, we propose nonlinear optimization method for feature matching from multiple view image. Typical solution of feature matching is by solving linear equation. However this solution has large error due to nonlinearity of image formation model. If typical nonlinear optimization method is used, complexity grows exponentially over the number of features. To make complexity lower, we use sparse Levenberg-Marquardt nonlinear optimization for matching of features over multiple view image.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.7
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• pp.1654-1667
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• 1996

The conventional fractal image compression methods have high computational complexity at encoding reduce PSNR at low bit rate and havehighly visible blocking effects in a reconstructed image. In this paper we propose a fractal image compression method based on disctete wavelet transform domain, which takes the absolute value of discrete wavelet transform coefficient, and assembles the discrete wavelet tranform coefficients of different highpass subbands corresponding to the same spatial block and then applies "0" encoding according to the energy of each range blocks. The proposed method improved PSNR at low bit rate and reduced computational complexity at encoding distinctly. Also, this method can achieve a blockless reconstructed image and perform hierarchical decoding without recursive constractive transformation. Computer simulations with several test images show that the proposed method shows better performance than convnetional fractal coding methods for encoding still pictures. pictures.

• Proceedings of the Korea Contents Association Conference
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• 2006.11a
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• pp.250-253
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• 2006

In this paper, we proposed a new method of the Adaptive steganography using complexity on bit planes of color image. Applying fixing threshold and variable length, if insert information into all bit plans, all bit plans showed different image quality. Therefore, we first defined the complexity on bit plane and data complexity, similarity insert information into bit plans. As a result, the proposed method increased the insertion capacity and improved the image quality than fixing threshold and variable length method.

• Journal of Korea Multimedia Society
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• v.20 no.11
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• pp.1750-1758
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• 2017

In super-resolution, various methods with Convolutional Neural Network(CNN) have recently been proposed. CNN based methods provide much higher image quality than conventional methods. Especially, VDSR outperforms other CNN based methods in terms of image quality. However, it requires a high computational complexity which prevents real-time processing. In this paper, the method to apply a deconvolution layer to VDSR is proposed to reduce computational complexity. Compared to original VDSR, the proposed method achieves the 4.46 times speed-up and its degradation in image quality is less than -0.1 dB which is negligible.

• Journal of Korea Multimedia Society
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• v.8 no.7
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• pp.961-973
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• 2005

In this paper, we proposed an adaptive steganography of color image using bit-planes and multichannel characteristics. Applying fixing threshold, if we insert information into all bit-planes of RGB channel, each channels showed different image quality. Therefore, we first defined the channel weight and the bit-plane weight to solve the fixing threshold problem of BPCS (bit-plane complexity steganography) method. We then proposed a new adaptive threshold method using the bit-plane weight of channels and the bit-plane complexity of cover image to increase insertion capacity adaptively In the experiment, we inserted information into the color images with the same image quality and same insertion capacity, and we analyzed the Insertion capacity and image quality. As a result, the proposed method increased the insertion capacity and improved the image quality than BPCS method.

• Journal of the Korea Society of Computer and Information
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• v.18 no.10
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• pp.39-46
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• 2013

Recently, the mobile industries grow up rapidly and their performances are improved. So the usage of mobile devices is increasing in our life. Also mobile devices equipped with a high-performance camera, so the image stitching can carry out on the mobile devices instead of the desktop. However the mobile devices have limited hardware to perform the image stitching which has a lot of computational complexity. In this paper, we have proposed improved feature descriptor extraction and matching method for efficient image stitching on mobile environment. Our method can reduce computational complexity using extension of orientation window and reduction of dimension feature descriptor when feature descriptor is generated. In addition, the computational complexity of image stitching is reduced through the classification of matching points. In our results, our method makes to improve the computational time of image stitching than the previous method. Therefore our method is suitable for the mobile environment and also that method can make natural-looking stitched image.

• 한국정보디스플레이학회:학술대회논문집
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• 2009.10a
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• pp.1316-1318
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• 2009

Nonideality of LED lens and diffuser as well as crosstalk between backlights should be compensated because they have large effects on image qualities. The computation complexities of conventional compensations are greatly increased as resolution becomes higher. The block based compensation is proposed to alleviate the computation complexity considering backlight profiles and image pixel characteristics.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.7C
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• pp.681-686
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• 2009

In H.264/Ave, an intra prediction added to the P-frame coding slightly improves both of image quality and bit rate, but greatly increases an amount of computation. In order to reduce the increase in computation, this paper proposes an image contents based intra prediction coding using characteristics that the best intra block mode depends on the image content of a macro block. The proposed algorithm estimates the image content with image complexity and the best inter block mode, and then selects or excludes a intra block mode on the basis of it. The simulation results show that the proposed algorithm reduces average O.OldB in image quality, and increases average 0.38% in the bit rate, but reduces average 37.02% in computation time compared with the conventional algorithm.

• Journal of Korea Multimedia Society
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• v.14 no.8
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• pp.1000-1009
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• 2011

Image interpolation is a technique which estimates the non-allocated pixel values on image scale-transform. It requires minimum computational complexity and minimum image quality degradation on the interpolated resultant images. In this paper we propose an image interpolation method using iterative error estimation. The proposed method consists of the following five steps: loss-information computational step, loss-information estimation step, loss-information application step, error computation step, and error application step. The experimental results obtained show that the average PSNR is increased by 3.3dB, subjective image quality is enhanced and the minimum computation complexity is decreased by 83%. The proposed image interpolation algorithm may be helpful in various applications such as image reconstruction and enlargement.