• Journal of Korea Multimedia Society
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• v.14 no.8
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• pp.1000-1009
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• 2011

Image interpolation is a technique which estimates the non-allocated pixel values on image scale-transform. It requires minimum computational complexity and minimum image quality degradation on the interpolated resultant images. In this paper we propose an image interpolation method using iterative error estimation. The proposed method consists of the following five steps: loss-information computational step, loss-information estimation step, loss-information application step, error computation step, and error application step. The experimental results obtained show that the average PSNR is increased by 3.3dB, subjective image quality is enhanced and the minimum computation complexity is decreased by 83%. The proposed image interpolation algorithm may be helpful in various applications such as image reconstruction and enlargement.

• Journal of KIISE:Computer Systems and Theory
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• v.29 no.12
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• pp.680-686
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• 2002

In deep-submicron (BSM) design, coupling effects between wires on the bus cause serious problems such as crosstalk delay, noise, and power consumption. Most of the previous works on bus encoding are targeted either to minimize tile power consumption on bus or to minimize the crosstalk delay, but not both. In this paper, we propose a new bus encoding algorithm that minimizes the power consumption on bus and eliminates the crosstalk delay simultaneously. We formulate and solve the problem by minimizing a weighted sum of the self transition and cross-coupled transition activities on bus From experiments using a set of benchmark designs. it is shown that the proposed encoding technique consumes at least 15% less power over the existing techniques, while completely eliminating the crosstalk delay.

• The Journal of the Korea Contents Association
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• v.9 no.11
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• pp.309-315
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• 2009

Image reconstruction of Inverse Fourier Transform after Frequency Domain Data is filtered applies to Image signal acquired from MR. There are various kinds of image processing techniques; image preprocessing, image reconstruction, image compression, image restoration image mixture, noise and artifact elimination, and image quality improvement. In this paper, optimum filter applicable to diagnosis in clinic by comparing and analyzing the characteristics of the filter will be explained. Fermi-Dirac filter will improve the image quality better than the previous MR image.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2008.04a
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• pp.218-223
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• 2008

Cell-phone becomes a necessary communication device in modern society. However, a paging signal by a sound transducer often acts as an unpleasant noise, thus necessitating a paging signal by a vibration motor. The conventional flat type vibration motor uses three-phase windings with three phase coils. In this article, a new design of a vibration motor using a V connection with two phase coils is presented, increasing mass productivity. For electromagnetic field analysis, due to the motor symmetry, two-dimensional modeling can be implemented for fast computation, and performance is predicted by the finite element method. The winding distribution angle turns out to be the most important design parameter for the elimination of dead points, and a new coil configuration is suggested which has no adverse effect on motor size and weight. Experimental tests of vibration confirm the validity of the proposed design.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.5
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• pp.518-523
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• 2017

This paper proposes a novel denoising method based on non-local(NL) means. The NL-means algorithm is effective for removing an additive Gaussian noise, but the denoising parameter should be controlled depending on the noise level for proper noise elimination. Therefore, the proposed method optimizes the denoising parameter according to the noise levels. The proposed method consists of two processes: off-line and on-line. In the off-line process, the relations between the noise level and the denoising parameter of the NL-means filter are analyzed. For a given noise level, the various denoising parameters are applied to the NL-means algorithm, and then the qualities of resulting images are quantified using a structural similarity index(SSIM). The parameter with the highest SSIM is chosen as the optimal denoising parameter for the given noise level. In the on-line process, we estimate the noise level for a given noisy image and select the optimal denoising parameter according to the estimated noise level. Finally, NL-means filtering is performed using the selected denoising parameter. As shown in the experimental results, the proposed method accurately estimated the noise level and effectively eliminated noise for various noise levels. The accuracy of noise estimation is 90.0% and the highest Peak Signal-to-noise ratio(PSNR), SSIM value.

• Imaging Science in Dentistry
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• v.43 no.3
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• pp.185-190
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• 2013

Purpose: The aim of the present study was to evaluate the measurement accuracy of endodontic file length on periapical digital radiography after application of noise reduction digital enhancement. Materials and Methods: Thirty-five human single-rooted permanent teeth with canals measuring 20-24 mm in length were selected. ISO #08 endodontic files were placed in the root canals of the teeth. The file lengths were measured with a digital caliper as the standard value. Standard periapical digital images were obtained using the Digora digital radiographic system and a dental X-ray unit. In order to produce the enhanced images, the noise reduction option was applied. Two blinded radiologists measured the file lengths on the original and enhanced images. The measurements were compared by repeated measures ANOVA and the Bonferroni test (${\alpha}=0.05$). Results: Both the original and enhanced digital images provided significantly longer measurements compared with the standard value (P<0.05). There were no significant differences between the measurement accuracy of the original and enhanced images (P>0.05). Conclusion: Noise reduction digital enhancement did not influence the measurement accuracy of the length of the thin endodontic files on the digital periapical radiographs despite the fact that noise reduction could result in the elimination of fine details of the images.

• Journal of Veterinary Clinics
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• v.29 no.6
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• pp.494-497
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• 2012

A 6-year-old castrated male Miniature Pinscher dog was referred due to shaking, panting and inappropriate elimination during thunderstorms. The dog had noise phobia after a car accident two years ago. The intensity of the fear of noise, especially with thunderstorms, worsened during the past 3 months (thunderstorm season). Physical examination revealed hyperthermia, tachypnea (panting), mild tachycardia, and an elevated systolic blood pressure. Laboratory examination revealed mild polycythemia with a lower oxygen pressure and saturation. Based on the history, physical examination, and laboratory tests, the dog was diagnosed as a noise phobia concurrent with relative polycythemia. Treatment was initiated with behavior modification with desensitization, counter-conditioning, and medication. Music therapy was also used and appeared to be beneficial. Clinical signs including polycythemia are improved. This case indicates that relative polycythemia can be occurred by chronic mental stress, such as noise phobia in a dog.

• Journal of the Institute of Convergence Signal Processing
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• v.15 no.4
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• pp.135-140
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• 2014

As the digital image devices are widely used, interests in the software- and the hardware-related image processing become higher and the image processing techniques are applied in various fields such as object recognition, object detection, fingerprint recognition, and etc. For the edge detections Sobel, Prewitt, Laplacian, Roberts and Canny detectors are used and these existing methods can excellently detect the edges of the images without noise. However, in the images corrupted by the impulse noise, these methods are insufficent in noise elimination characteristics, showing unsatisfactory edge detection. Therefore in this paper, in order to obtain excellent edge detection characteristics in the corrupted image by the impulse noise, an detection algorithm is porposed, which uses the central pixel of mask divided by four regions along the axis, calculates the estimated mask according to the representing pixel values in each regions, and detects the final edges by applying the estimates mask and the new directional one.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.05a
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• pp.790-792
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• 2017

As the demand of digital image processing devices has been rapidly increased recently, the excellent image quality is required. However, degradation can be occurred with multiple causes during transmission and processing process. Therefore, the needs to eliminate the noise are increased and the noise elimination technology became the major study area. Therefore, image restoration algorithm was suggested to apply the filter differently by edge and non-edge areas, using modified edge detection with preprocessing process so as to relieve the effect of additive white Gaussian noise(AWGN) which is added in the image, in this article. In addition, it was compared with the existing methods using peak signal to noise ratio(PSNR) as the objective determination standard of the improvement effect.

• Journal of Biomedical Engineering Research
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• v.19 no.3
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• pp.269-278
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• 1998

This paper describes a development of efficient stress ECG signal analysis algorithm. The algorithm consists of wavelet adaptive filter(WAF), QRS detector and ST segment detector. The WAF consists of a wavelet transform and an adaptive filter. The wavelet transform decomposed the ECG signal into seven levels using wavelet function for each high frequency bank and low frequency bank. The adaptive filter used the signal of the seventh lowest frequency band among the wavelet transformed signals as primary input. For detection of QRS complex, we made summed signals that are composed of high frequency bands including frequency component of QRS complex and applied the adaptive threshold method changing the amplitude of threshold according to RR interval. For evaluation of the performance of the WAF, we used two baseline wandering elimination filters including a standard filter and a general adaptive filter. WAF showed a better performance than compared filters in the noise elimination characteristics and signal distortion. For evaluation of WAF showed a better performance than compared filters in the noise elimination characteristics and signal distortion. For evaluation of results of QRS complex detection, we compared our algorithm with existing algorithms using MIT/BIH database. Our algorithm using summed signals showed the accuracy of 99.67% and the higher performance of QRS detection than existing algorithms. Also, we used European ST-T database and patient data to evaluate measurement of the ST segment and could measure the ST segment adaptively according to change of heart rate.