• Journal of Korea Multimedia Society
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• v.3 no.4
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• pp.365-371
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• 2000

To restore image degraded by out-of-focus blur and additive noise, an iterative restoration is used. Acceleration parameter is usually applied equally to all over the image without considering the local characteristics of degraded images. As a result, the conventional methods are not effective in restoring severely degraded edge region and shows slow convergence rate. To solve this problem we propose an adaptive iterative restoration according to local degradation, in which the acceleration parameter has low value in flat region that is less degraded and high value in edge region that is more degraded. Through experiments, we verified that the proposed method showed better results with fast convergence rate, showed Visually better image in edge region and lower MSE than the conventional methods.

• International Journal of Precision Engineering and Manufacturing
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• v.8 no.3
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• pp.64-70
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• 2007

Of all the rapid tooling (RT) methods currently available, thick-layer laminated tooling is the most suitable for large-scale, low-cost dies and molds. Currently, the determination of a lamina's contour or profile and the associated slicing algorithms are based on existing rapid prototyping (RP) data manipulation technology. This paper presents a new adaptive slicing algorithm developed exclusively for profiled edge laminae (PEL) tooling PEL tooling is a thick-layer RT technique that involves the assembly of an array of laminae, whose top edges are simultaneously profiled and beveled using a line-of-sight cutting method based on a CAD model of the intended tool surface. The cutting profiles are based on the intersection curve obtained directly from the CAD model to ensure geometrical accuracy. The slicing algorithm determines the lamina thicknesses that minimize the dimensional error using a new tool shape error index. At the same time, the algorithm considers the available lamination thicknesses and desired lamina interface locations. We demonstrate the new slicing algorithm by developing a simple industrial PEL tool based on a CAD part shape.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.9B
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• pp.1588-1595
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• 2000

To restore image degraded by out-of-focus blur and additivie noise a regularized iterative restoration is used. In concentional method, regularization is usually applied to all over the image without considering the local characteristics of image. As a result, ringing artifacts appear in edge regions and the noise amplification is introduced in flat regions. To solve this problem we propose an adaptive regularization iterative restoration using directional regularization operator considering edges in four directions and the regularization operator with on direction for flat regions. We verified that the proposed method show better results in the suppression of the noise amplification in flat regions, and introduced less ringing artifacts in edge regions. As a result it showed visually better image and improved better ISNR further than the conventional methods.

• 전자공학회논문지 IE
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• v.47 no.2
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• pp.27-31
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• 2010

In this paper, a predictor switching algorithm for lossless compression is proposed. It uses adaptively one of two predictors using errors obtained by MED(median edge detector) and GAP(gradient adaptive prediction). The reduced error is measured by existing entropy method. Experimental results show that the proposed algorithm can compress higher than existing predictive methods.

• Journal of Korea Multimedia Society
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• v.4 no.3
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• pp.222-229
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• 2001

Many techniques have been proposed for digital image enlargement, which use spatially neighbored pixels information in a still image. In this paper, we propose the digital image interpolation method that improves edge characteristics by selectively transposing the sub-windows of pseudomedian filter, which results in relatively better performance than others. We have simulated the proposed algorithm using Visual C++ and verified performance of the algorithm by PSNR(Peak signal Noise Ratio) and edge characteristics. Finally, we have designed the adaptive pseudomedian by using synopsys VHDL(Very high speed integrated circuit Hardware Description Language).

• The Transactions of the Korea Information Processing Society
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• v.7 no.7
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• pp.2254-2263
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• 2000

This paper proposes an efficient predictive image-compression technique based on vector quantization of blocks of pels. In the proposed method edge contents of blocks control the selection of predictors and block shapes as well. The maximum number of bits assigned to quantizers has been in creased to 3bits/pel from 1/5bits/pel, the setting employed by forerunners in predictive vector quantization of images. This increase prevents the saturation in SNR observed in their results in high bit rates. The variable block shape is instrumental in eh reconstruction of edges. The adaptive procedure is controlled by means of he standard deviation ofp rediction errors generated by a default predictor; the standard deviation address a decision table which can be set up beforehand. eh proposed method is characterized by overall improvements in image quality over A-VQ-PE and A-DCT VQ, both of which are known for their efficient use of vector quantizers.

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.1903-1906
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• 2003

This paper proposes an adaptive regularized noise smoothing algorithm for range image using the area decreasing flow method, which can preserve meaningful edges during the smoothing process. Although the area decreasing flow method can easily smooth Gaussian noise, it has two problems; ⅰ) it is not easy to remove impulsive noise from observed range data, and ⅱ) it is also difficult to remove noise near edge when the adaptive regularization is used. In the paper, therefore, the second smoothness constraint is addtionally incorporated into the existing regularization algorithm, which minimizes the difference between the median filtered data and the estimated data. As a result, the Proposed algorithm can effectively remove the noise of dense range data with edge preserving.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1997.06a
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• pp.107-112
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• 1997

This paper proposes the regularized constrained iterative image restoration algorithms which apply new space-adaptive methods to degraded image signals, and analyzes the convergence condition of the proposed algorithm. First, we introduce space-adaptive regularization operators which change according to edge characteristics of local images in order to effectively prevent the restored edges and boundaries from reblurring. And, pseudo projection operator is used to reduce the ringing artifact which results from extensive amplification of noise components in the restoration process. The analysed algorithm is stable convergent to the fixed point. According to the experimental results for various signal-to-noise ratios(SNR) and blur models, the proposed algorithms other methods and is robust to noise effects and edge reblurring by regularization especially.

• Proceedings of the KIEE Conference
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• 2001.04a
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• pp.167-170
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• 2001

A three dimensional adaptive finite element analysis algorithm is developed. In the method, the edge elements are used for field analysis, and the local error. In each element is estimated from the fact that the magnetic field should satisfy. The continuity condition at the interface of the two adjacent elements. Based on the estimated error, the elements which are considered to have big error are divided into several elements using the bisection method. The effectiveness of the developed algorithm is proved through numerical examples.

• Proceedings of the IEEK Conference
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• 2007.07a
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• pp.251-252
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• 2007

The thesis proposed the Text Extraction Algorithm which is a text extraction algorithm which uses the Coiflet Wavelet, YCbCr Color model and the close curve edge feature of adaptive LoG Operator in order to complement the demerit of the existing research which is weak in complexity of background, variety of light and disordered line and similarity of text and background color. This thesis is simulated with natural images which include naturally text area regardless of size, resolution and slant and so on of image. And the proposed algorithm is confirmed to an excellent by compared with an existing extraction algorithm in same image.