• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.2
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• pp.156-160
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• 2014

Thresholding in frequency domain is a simple and effective noise reduction technique. Determination of the threshold is critical to the image quality. The optimal threshold minimizing the Mean Square Error (MSE) is chosen adaptively in the wavelet domain; we utilize an equation of the MSE for the soft-thresholded signal and the histogram of wavelet coefficients of the original image and noisy image. The histogram of the original signal is estimated through the deconvolution assuming that the probability density functions (pdfs) of the original signal and the noise are statistically independent. The proposed method is quite general in that it does not assume any prior for the source pdf.

• Proceedings of the IEEK Conference
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• 2005.11a
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• pp.387-390
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• 2005

Parameter estimation for the probability model of wavelet coefficients is essential to the wavelet-domain interpolation. However, phase uncertainty, one well-known drawback of the orthogonal wavelet transforms, make it difficult to estimate parameters. In this paper, we exploit a phase shifting matrix in order to improve the accuracy of estimation. Nonlinear modeling to capture the interscale characteristics is also described. The experimental results show that the proposed method outperforms the previous wavelet-domain interpolation method as well as the conventional bicubic method.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2001.12a
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• pp.5-9
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• 2001

In this paper, we propose the new audio watermarking method and can be used on line processing. Instead of the wavelet transform, we use the integer wavelet transform for the reduction of the computational load. The watermark associated with the chi-square distribution is inserted into the signal on the integer wavelet domain. When extracting the watermark, the spread spectrum methods are used with the coefficients associated with the covariance sequence. We show that the chi-square distribution is a good tool for the spread spectrum method on the wavelet domain. This watermarking technique may be used for the control of the electrical product which can be controlled with the hidden signals and can be moved according to the audible signals simultaneously.

• 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.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.1B
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• pp.120-127
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• 2000

In this paper, we propose multispectral image compression using classified interband prediction and vector quantization in wavelet domain. This method classifies each region considering reflection characteristics of each band in image data. In wavelet domain, we perform the classified intraband VQ to remove intraband redundancy for a reference band image that has the lowest spatial variance and the best correlation with other band. And in wavelet domain, we perform the classifled interband prediction to remove interband redundancy for the remaining bands. Then error wavelet coefficients between original image and predicted image are intraband vector quantized to reduce prediction error. Experiments on remotely sensed satellite image show that coding efficiency of theproposed method is better than that of the conventional method.

• Journal of Korea Multimedia Society
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• v.11 no.4
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• pp.443-453
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• 2008

In this paper, the 1-level DWT(Discrete Wavelet Transform) coefficients of a binary logo image are used as the watermark. The watermark should be inserted in the same band which is equivalent to the host image when the watermark is inserted in the wavelet domain. This is the image fusion of the proposed watermarking method. The watermark is inserted in relatively significant coefficients after the insertion area is defined. The more significant coefficients have the important information because they are identified as the edge and major surface in images. The significant coefficients are defined when their absolute value exceeds the threshold. The standard deviation is used as the weight value of watermark insertion in order to strengthen the weight of the watermark insertion according to the value of the coefficients. The proposed watermarking method is an adaptive scheme, and the proposed two detection algorithms can be adaptively used when the watermarked image is distorted by cropping, filtering, or compression.

• Proceedings of the IEEK Conference
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• 2002.06d
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• pp.85-88
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• 2002

In this paper, the proposed watermark algorithm is based on energy distribution of the subband coefficients in the frequency domain and edge of the original image in the spacial domain. Out of these information, the KeyMap which decides the embedded position of watermark is produced. And then the binary watermark is embedded into the wavelet coefficient of LL3 subband using KeyMap and LFSR(Linear Feedback Shift Register).

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.7
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• pp.1613-1623
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• 1996

In this paper, an image coding scheme using removal of isolated coefficients and quadtree structure in wavelet transformed domain, is suggested. The number of significant coefficients can be reduced by quantizing in different stages according to the weights of the each band. The quadtree structure preseves the location information while significantly reducing the number of bits required to represent the locality of an image. To increase the efficienty of the wavelet transformed images using quadtree, the energy of the isolated coefficients is analyzed and those with low energy are eliminated. Furthermore, to control the bit rate the entropy of each block is sorted according to its energy concentration and the number of bits required for encoding, and the blocks with low energy are removed to achieve the desired compression rate.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.6
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• pp.19-26
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• 2005

Image interpolation in the wavelet domain usually takes advantage of the probabilistic models for the intrascale statistics and the interscale dependency. In this paper, we adopt the linear model for the absolute values of wavelet coefficients of interpolated image across scale to estimate the variances of extrapolated bands. The proposed algorithm uses randomly generated wavelet coefficients based on the estimated parameters for probabilistic model. Random number generation according to the estimated probabilistic model may induce the 'salt and pepper' noise in subbands. We reduce the noise power by Wiener filtering. We observe that the proposed method generates the histogram of the subband coefficients similar to the that of original image. Experimental results show that our method outperforms the previous wavelet-domain interpolation method as well as the conventional bicubic method.

• MALSORI
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• no.61
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• pp.63-74
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• 2007

Discrimination of music and speech from the multimedia signal is an important task in audio coding and broadcast monitoring systems. This paper deals with the problem of feature parameter extraction for discrimination of music and speech. The wavelet transform is a multi-resolution analysis method that is useful for analysis of temporal and spectral properties of non-stationary signals such as speech and audio signals. We propose new feature parameters extracted from the wavelet transformed signal for discrimination of music and speech. First, wavelet coefficients are obtained on the frame-by-frame basis. The analysis frame size is set to 20 ms. A parameter $E_{sum}$ is then defined by adding the difference of magnitude between adjacent wavelet coefficients in each scale. The maximum and minimum values of $E_{sum}$ for period of 2 seconds, which corresponds to the discrimination duration, are used as feature parameters for discrimination of music and speech. To evaluate the performance of the proposed feature parameters for music and speech discrimination, the accuracy of music and speech discrimination is measured for various types of music and speech signals. In the experiment every 2-second data is discriminated as music or speech, and about 93% of music and speech segments have been successfully detected.