• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.12C
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• pp.1214-1221
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• 2005

In this paper, we propose a digital watermarking method for still images, in which the human visual system (HVS) is used in the discrete cosine transform (DCT) domain. The modulation transfer function (MTF) of the HVS model is employed to increase the invisibility of the inserted watermark in images. The proposed watermarking method is shown to be robust to several common image processing techniques, including lowpass filtering and cropping. Also, using the energy relationship of the DCT, we derive the equation that directly computes the watermark weighting factor in the DCT domain for the specified peak signal to noise ratio (PSNR) of the still image and the length of watermark to be inserted. The difference between desired PSNR and PSNR in spatial domain is within 0.07dB for the 7 test images.

• KIPS Transactions on Software and Data Engineering
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• v.8 no.4
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• pp.171-178
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• 2019

The use of anti-scatter grids in radiographic imaging has the advantage of preventing the image distortion caused by scattered radiation. However, it carries the side effect of leaving artifacts in the X-ray image. In this paper, we propose a grid line suppression technique using discrete cosine transform(DCT). In X-ray images, the grid lines have different characteristics depending on the shape of the object and the area of the image. To solve this problem, we adopt the DCT transform based on a dynamic segmentation, and propose a filter transfer function for each individual segment. An algorithm for detecting the band of grid lines in frequency domain and a band stop filter(BSF) with a filter transfer function of a combination of Kaiser window and Butterworth filter have been proposed. To solve the blocking effects, we present a method to determine the pixel values using multiple structured images. The validity of the proposed theory has been evaluated from the experimental results using 140 X-ray images.

• Proceedings of the KSPS conference
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• 2005.04a
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• pp.53-56
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• 2005

In this paper, we propose a transformation based robust adaptation technique that uses the maximum mutual information(MMI) estimation for the objective function and the linear spectral transformation(LST) for adaptation. LST is an adaptation method that deals with environmental noises in the linear spectral domain, so that a small number of parameters can be used for fast adaptation. The proposed technique is called MMI-LST, and evaluated on TIMIT and FFMTIMIT corpora to show that it is advantageous when only a small amount of adaptation speech is used.

• Journal of Biomedical Engineering Research
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• v.11 no.1
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• pp.83-88
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• 1990

A New speech processing algorithm using neural networks is proposed. We transform input data into frequency domain and process them by neural networks of 22 output neurons which have Bark scale on the ground that the Bark scale is similiar with that of the characteristics of human cochlea. An utilized neural network is multilayer perceptron, and the characteristics of cochlea have it trained by error back propagation learning algorithm. The trained neural networks suffices functions of human cochlea including the effects of automatic gain control, compression and equalization. Simulation results show that the proposed speech processing algorithm has good performance in automatic gain control, compression and equalization.

• The Transactions of the Korea Information Processing Society
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• v.7 no.11
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• pp.3566-3575
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• 2000

In this paper, we propose an simple and efficient method to estunate the camera operation by using compressed information, which is extracted diracily from MPEG2 stream without complete decoding. In the method, the motion vector is converted into approximate optical flow by using the feature of predicted frame, because the motion vector in MPEG2 video stream is not regular sequene. And they are used to estimate the camera operation, which consist of pan, and zoom by Hough transform technique. The method provided better results than the least square method for video stream of basketball and socer games. The proposed method can have a reduced computational complexity because the information is directiv abtained in compressed domain. Additionally it can be a useful technology in content-based searching and analysis of video information. Also, the estimatd cameral operationis applicable in searching or tracking objects in MPEG2 video stream without decoding.

• Journal of the Institute of Convergence Signal Processing
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• v.3 no.3
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• pp.36-40
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• 2002

In this paper, we proposed a digital watermarking method based on the edge-wavelet transform to protect digital contents copyrights. We find out the optimal watermark insertion region and the proper amount of watermark in order to satisfy robustness and imperceptibility against various attacks such as noise, compression, collusion, clipping, scaling. Especially through this experiment, we could find out the adequate location of watermark insertion and proper amount of watermark and it is also viewed to satisfy robustness and imperceptibility in the lower frequency region with small watermark quantity.

• Journal of Information Processing Systems
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• v.12 no.1
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• pp.35-45
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• 2016

To resolve the problems of Poisson/impulse noise, blurriness, and sharpness in degraded X-ray images, a novel and efficient enhancement algorithm based on X-ray image fusion using a discrete wavelet transform is proposed in this paper. The proposed algorithm consists of two basics. First, it applies the techniques of boundary division to detect Poisson and impulse noise corrupted pixels and then uses the Wiener filter approach to restore those corrupted pixels. Second, it applies the sharpening technique to the same degraded X-ray image. Thus, it has two source X-ray images, which individually preserve the enhancement effects. The details and approximations of these sources X-ray images are fused via different fusion rules in the wavelet domain. The results of the experiment show that the proposed algorithm successfully combines the merits of the Wiener filter and sharpening and achieves a significant proficiency in the enhancement of degraded X-ray images exhibiting Poisson noise, blurriness, and edge details.

• 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 Information Processing Systems
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• v.12 no.4
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• pp.765-778
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• 2016

In watermarking schemes, the discrete wavelet transform (DWT) is broadly used because its frequency component separation is very useful. Moreover, LU decomposition has little influence on the visual quality of the watermark. Hence, in this paper, a novel blind watermark algorithm is presented based on LU transform and DWT for the copyright protection of digital images. In this algorithm, the color host image is first performed with DWT. Then, the horizontal and vertical diagonal high frequency components are extracted from the wavelet domain, and the sub-images are divided into $4{\times}4$ non-overlapping image blocks. Next, each sub-block is performed with LU decomposition. Finally, the color image watermark is transformed by Arnold permutation, and then it is inserted into the upper triangular matrix. The experimental results imply that this algorithm has good features of invisibility and it is robust against different attacks to a certain degree, such as contrast adjustment, JPEG compression, salt and pepper noise, cropping, and Gaussian noise.

• Journal of the Institute of Convergence Signal Processing
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• v.8 no.2
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• pp.91-97
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• 2007

Points of sharp variations in signals are the most important factors when analyzing the features of signals. And in the image, edges include diverse information such as the locations, shape and material. There have been a variety of researches on edge detections, among them, methods based on convolution in the spatial domain have been most popular. However at the early stage of the method, if the noise and many kinds of edges exist in the image, it is not easy to separate edges selectively from corrupted images by noise. In meantime, the wavelet transform for multiscale edge detection is being applied widely to analyze the properties of images in various fields. In this paper, we suggest a robust wavelet-based method, which selectively detects line-edge elements from images in the presence of noise.