• Journal of the Institute of Convergence Signal Processing
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• v.4 no.2
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• pp.46-52
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• 2003

In this paper, the wavelet watermarking algorithm based on adaptive weight MASK processing as a watermark embedded-method for Copyright Protection of Digital contents is Proposed. Because watermark induce as a noise of original image, the watermark size should be limited for preventing quality losses and embedding watermark into images. Therefore, it should be preserve the best condition of the factors, robustness, capacity and visual quality. Tn order to solve this problem, we propose watermarking embedded method by applying adaptive weight MASK to the algorithm and optimize its efficiency. In that result, the watermarked images are improved about external attack. Specifically, correlation coefficient has over 0.8 on both modifications of brightness and contrast. Also, correlation coefficient of wavelet compression of embedded watermark last by over 0.65.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.9
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• pp.106-113
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• 2015

This paper integrates human visual system (HVS) characteristics into compressed sensing recovery of color images. The proposed visual weighting of each color channel in group-sparsity minimization not only pursues sparsity level of image but also reflects HVS characteristics well. Additionally, an edge-preserving filter is embedded in the scheme to remove noise while preserving edges of image so that quality of reconstructed image is further enhanced. Experimental results show that the average PSNR of the proposed method is 0.56 ~ 4dB higher than that of the state-of-the art group-sparsity minimization method. These results prove the excellence of the proposed method in both terms of objective and subjective qualities.

• Journal of Broadcast Engineering
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• v.15 no.4
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• pp.527-539
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• 2010

Most video coding systems use YCbCr color space for their inputs, but RGB space is more preferred in the field of high fidelity video because the compression gain from YCbCr becomes disappeared in the high quality operation region. In order to improve the coding performance of RGB video signal, this paper presents an adaptive frequency-selective weighted prediction algorithm. Based on the sign agreement and the strength of frequency-domain correlation of residual color planes, the proposed scheme adaptively selects the frequency elements as well as the corresponding prediction weights for better utilization of inter-plane correlation of RGB signal. Experimental results showed that the proposed algorithm improves the coding gain of around 13% bitrate reduction, on average, compared to the common mode of 4:4:4 video coding in the state-of-the-art video compression standard, H.264/AVC.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.10a
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• pp.504-505
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• 2017

Existing morpheme analyzers classify the words used in writing documents. A system for extracting sentences and paragraphs based on a morpheme analyzer is being developed. However, there are very few systems that compress documents and extract important paragraphs. The algorithm proposed in this paper calculates the weights of the keyword written in the document and extracts the paragraphs containing the keyword. Users can reduce the time to understand the document by reading the paragraphs containing the keyword without reading the entire document. In addition, since the number of extracted paragraphs differs according to the number of keyword used in the search, the user can search various patterns compared to the existing system.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.11
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• pp.2133-2138
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• 2017

The analysis of existing XML documents and other documents was centered on words. It can be implemented using a morpheme analyzer, but it can classify many words in the document and cannot grasp the core contents of the document. In order for a user to efficiently understand a document, a paragraph containing a main word must be extracted and presented to the user. The proposed system retrieves keyword in the normalized XML document. Then, the user extracts the paragraphs containing the keyword inputted for searching and displays them to the user. In addition, the frequency and weight of the keyword used in the search are informed to the user, and the order of the extracted paragraphs and the redundancy elimination function are minimized so that the user can understand the document. The proposed system can minimize the time and effort required to understand the document by allowing the user to understand the document without reading the whole document.

• Journal of the Institute of Convergence Signal Processing
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• v.10 no.1
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• pp.49-59
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• 2009

In this paper a watermarking algorithm is proposed to optimize the capacity of the digital watermark insertion in an experimental threshold using the characteristics of human visual system(HVS), adaptive scale factors, and weight functions based on discrete wavelet transform. After the original image is decomposed by a 3-level discrete wavelet transform, the watermarks for capacity optimization are inserted into all subbands except the baseband, by applying the important coefficients from the experimental threshold in the wavelet region. The adaptive scale factors and weight functions based on HVS are considered for the capacity optimization of the digital watermark insertion in order to enhance the robustness and invisibility. The watermarks are consisted of gaussian random sequences and detected by correlation. The experimental results showed that this algorithm can preserve a fine image quality against various attacks such as the JPEG lossy compression, noise addition, cropping, blurring, sharpening, linear and non-linear filtering, etc.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.37 no.1
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• pp.55-63
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• 2000

This paper investigated the sub-region compression effect of the three dimensional DCT(3D-DCT) using the difference component(DC) of inter-frame in images. The proposed algorithm are the method that obtain compression effect to divide the information into subband after 3D-DCT, the data appear the type of cubic block(8${\times}$8${\times}$8) in eight difference components per unit. In the frequence domain that transform the eight differential component frames into eight DCT frames with components of both spatial and temporal frequencies of inter-frame, the image data are divided into frame component(8${\times}$8 block) of time-axis direction into 4${\times}$4 sub block in order to effectively obtain compression data because image components are concentrate in corner region with low-frequency of cubic block. Here, using the weight of sub block, we progressed compression ratio as consider to adaptive sub-region of low frequency part. In simulation, we estimated compression ratio, reconstructed image resolution(PSNR) with the simpler image and the complex image contained the higher frequency component. In the result, we could obtain the high compression effect of 30.36dB(average value in the complex-image) and 34.75dB(average value in the simple-image) in compression range of 0.04~0.05bpp.

• Journal of Korea Multimedia Society
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• v.8 no.4
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• pp.516-524
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• 2005

In this paper, a new watermarking scheme based on the POCS theory and human visual system is proposed. Using the POCS theory, watermarks are embedded into imperceptible image regions such as edge and strong texture area in the spatial domain. Also it is inserted into middle frequency band in the transform domain to achieve the robustness against compression and filtering, etc. In addition, different gain factors are employed into blocks classified by considering texture masking effect. By doing so, the proposed method has a novel property of having both the imperceptibility and the robustness simultaneously. Simulation results show that the proposed method has an excellent performance better than conventional approaches.

• Journal of IKEEE
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• v.23 no.4
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• pp.1408-1414
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• 2019

Deep artificial neural network with transfer learning is applied to compressed sensing cardiovascular MRI. Transfer learning is a method that utilizes structure, filter kernels, and weights of the network used in prior learning for current learning or application. The transfer learning is useful in accelerating learning speed, and in generalization of the neural network when learning data is limited. From a cardiac MRI experiment, with 8 healthy volunteers, the neural network with transfer learning was able to reduce learning time by a factor of more than five compared to that with standalone learning. Using test data set, reconstructed images with transfer learning showed lower normalized mean square error and better image quality compared to those without transfer learning.

• Journal of Broadcast Engineering
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• v.5 no.2
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• pp.167-175
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• 2000

Compressed bitstreams generated by an MPEG-2 video encoder (or digital TV picture transmission are quite sensitive to channel errors. Due to the coding structure of the MPEG-2 video compression algorithm, a single bit error can affect not only the current Picture frame but also succeeding frames. Error concealment algorithms attempt to repair damaged portions of the picture by exploiting spatial and temporal redundancies in the correctly received and reconstructed video frames. In this paper, we analyze the effect of channel errors in MPEG-2 video bitstreams and estimate lost motion vectors by exploiting temporal redundancies in the video frames. Motion vectors can be estimated from the vertically adjacent extended region of lost macroblocks. Finally, we conceal the damaged macroblocks by compensating the displacement with the estimated motion vectors. Simulation results demonstrate that both the weighted sum algorithm and the extension matching algorithm achieve good performance in terms of PSNR values as well as subjective image quality.