• ETRI Journal
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• v.32 no.2
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• pp.336-338
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• 2010

A macroblock-level deblocking method is proposed for H.264/AVC, in which blocking artifacts are effectively eliminated in the discrete cosine transform domain at the macroblock encoding stage. Experimental results show that the proposed algorithm outperforms conventional H.264 in terms of coding efficiency, and the bitrate saving is up to 5.7% without reconstruction quality loss.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.5
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• pp.84-95
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• 2011

In this paper, we present a deblocking algorithm that removes grid and staircase noises, which are called "blocking artifacts", occurred in the compressed satellite images. Particularly, the given satellite images are compressed with equal quantization coefficients in row according to region complexity, and more complicated regions are compressed more. However, this approach has a problem that relatively less complicated regions within the same row of complicated regions have blocking artifacts. Removing these artifacts with a general deblocking algorithm can blur complex and undesired regions as well. Additionally, the general filter lacks in preserving the curved edges. Therefore, the proposed algorithm presents an adaptive filtering scheme for removing blocking artifacts while preserving the image details including curved edges using the given quantization step size and content analysis. Particularly, WLFPCA (weighted lowpass filter using principle component analysis) is employed to reduce the artifacts around edges. Experimental results showed that the proposed method outperforms SA-DCT in terms of subjective image quality.

• Proceedings of the Korean Information Science Society Conference
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• 2010.06a
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• pp.242-243
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• 2010

Reducing compression artifacts such as ringing and blocking is one of important issues to improve a visual quality of a JPEG compressed image. In this paper, we propose a new post processing technique based on bilateral filtering (BF), which is one of the techniques that are used to reduce compression artifacts. An important issue with the application of the BF is the selection of the filter parameters, which affects the result significantly. In this work, we suggest a new method to select the filter parameter automatically. In addition to artifact reduction using the BF, a contrast enhancement is performed to overcome the contrast loss problem due to compression. The experimental result shows that the proposed approach can alleviate the artifacts efficiently.

• Journal of Korea Multimedia Society
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• v.25 no.1
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• pp.29-38
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• 2022

Although image compression is one of the essential technologies to transmit image data on a variety of surveillance and mobile healthcare applications, it causes unnecessary compression artifacts such as blocking and ringing artifacts by the lossy compression in the limited network bandwidth. Recently, image restoration methods using convolutional neural network (CNN) show the significant improvement of image quality from the compressed images. In this paper, we propose Image Denoising Convolutional Neural Networks (IDCNN) to reduce the compression artifacts for the purpose of improving the performance of object classification. In order to evaluate the classification accuracy, we used the ImageNet test dataset consisting of 50,000 natural images and measured the classification performance in terms of Top-1 and Top-5 accuracy. Experimental results show that the proposed IDCNN can improve Top-1 and Top-5 accuracy as high as 2.46% and 2.42%, respectively.

• The Transactions of the Korea Information Processing Society
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• v.4 no.4
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• pp.1121-1131
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• 1997

In video coding at high compression rate, factal compression schemes in spatial domain have outstanding blocking artifacts and compression schemes in wavelet transform domain have rinfing artifacts at edges. In order to compensate these disadvantages, we propose a fractal video coding in wavelet transrorm domain which leads to clear edges without blocking atrifacts even at high bompression rate. The proposed method performs variable block sized motion estimation by using correlation among different subbands. Then the wavelet coefficients which are not enoded dffectively by the motion estimation are compressed by inter-frame fractal coding which predicts fine scale subbands hierarchically from the next coarser scale subbands. Computer sumulations with sev-eral test images wequences show that the proposed method shows better performance than the conventional video coding methods using fractal and wavelet.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1996.06a
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• pp.223-227
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• 1996

In this paper we propose an adaptive fast image restoration filter, which is suitable for reducing the blocking artifacts in the compressed image in real-time. The proposed restoration filter is based on the observation that quantization operation in a series of coding process is a nonlinear and many-to-one mapping operator. And then we propose an approximated version of constrained optimization technique as a restoration process for removing the nonlinear and space varying degradation operator. We also propose a novel block classification method for adaptively choosing the direction of a highpass filter, which serves as a constraint in the optimization process. The proposed classification method adopts the bias-corrected maximized likelihood, which is used to determine the number of regions in the image for the unsupervised segmentation. The proposed restoration filter can be realized either in the discrete Fourier transform domain or in the spatial domain in the form of a truncated finite impulse response (FIR) filter structure for real-time processing. In order to demonstrate the validity of the proposed restoration filter experimental results will be shown.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.178-180
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• 2004

In this work, we propose new method of sigma filtering for efficient filtering and preserving edge regions in DCT Domain. In block-based image compression technique, the image is first divided into non-overlapping $8{\times}8$ blocks. Then, the two-dimensional DCT is computed for each $8{\times}8$ block. Once the DCT coefficients are obtained, they are quantized using a specific quantization table. Quantization of the DCT coefficients is a lossy process, and in this step, noise is added. In this work, we combine IDCT matrix and filter matrix to a new matrix to simplify filtering process to remove noise after IDCT in spatial domain, for each $8{\times}8$ DCT coefficient block, we determine whether this block is edge or homogeneous region. If this block is edge region, we divide this $8{\times}8$ block into four $4{\times}4$ sub-blocks, and do filtering process for sub-blocks which is homogeneous region. By this process, we can remove blocking artifacts efficiently preserving edge regions at the same time.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.9
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• pp.4467-4486
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• 2016

Discrete cosine transform (DCT) based JPEG standard significantly improves the coding efficiency of image compression, but it is unacceptable event in serious blocking artifacts at low bit rate and low efficiency of high-definition image. In the light of all phase digital filtering theory, this paper proposes a novel transform based on discrete sine transform (DST), which is called all phase discrete sine biorthogonal transform (APDSBT). Applying APDSBT to JPEG scheme, the blocking artifacts are reduced significantly. The reconstructed image of APDSBT-JPEG is better than that of DCT-JPEG in terms of objective quality and subjective effect. For improving the efficiency of JPEG coding, the structure of JPEG is analyzed. We analyze key factors in design and evaluation of JPEG compression on the massive parallel graphics processing units (GPUs) using the compute unified device architecture (CUDA) programming model. Experimental results show that the maximum speedup ratio of parallel algorithm of APDSBT-JPEG can reach more than 100 times with a very low version GPU. Some new parallel strategies are illustrated in this paper for improving the performance of parallel algorithm. With the optimal strategy, the efficiency can be improved over 10%.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.3 s.309
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• pp.1-8
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• 2006

In this paper, we propose a new post-processing method, based on the theory of the projection onto convex sets (POCS) to reduce the blocking artifacts in decoded images. We propose a few smoothness constraint set (SCS) and its projection operator in the wavelet transform (WT) domain to remove unnecessary high-frequency components caused by blocking artifacts. We also propose a new method to find and preserve the original high frequency components of the image edge. Experimental results show that the proposed method can not only achieve a significantly enhanced subjective quality, but also have the PSNR improvement in the output image.

• Journal of the Semiconductor & Display Technology
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• v.8 no.3
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• pp.45-50
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• 2009

Recently, block-based transforms, like discrete cosine transform (DCT), have been widely used in image and video coding standards, but block-based transforms have a weak point with blocking effect. However, the integer lapped orthogonal transform (ILOT) is a tool for block-based coding with bases functions that overlap near blocks, so it has a strong point against blocking effect. Although it has slightly higher arithmetic complexity than the DCT, the coding gain is significantly higher with much less blocking artifacts. This paper introduces the integer lapped orthogonal transforms and discrete cosine transform. And we compare the performance of DCT with ILOT which is proposed a new efficient method for image coding applications.