• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.7
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• pp.1383-1388
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• 2016

Although image signal processing is used in many fields, degradation takes place in the process of transmitting image data by several causes. CWMF, A-TMF, and AWMF are the typical methods to eliminate noises from image data damaged under salt and pepper noise environment. However, those filters are not effective for noise rejection under highly dense noise environment. In this respect, the present study proposed an algorithm to remove in salt and pepper noise. In case the center pixel is determined to be non-noise, it is replaced with original pixel. In case the center pixel is noise, it segments local mask into 4 directions and uses linear interpolation to estimate original pixel. And then it applies spatial weight to the estimated pixel. The proposed algorithm shows a high PSNR of 24.56[dB] for House images that had been damaged of salt and pepper noise(P = 50%), compared to the existing CWMF, A-TMF and AWMF there were improvements by 16.46[dB], 12.28[dB], and 12.32[dB], respectively.

• Journal of Sensor Science and Technology
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• v.8 no.1
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• pp.32-37
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• 1999

A capacitance-type humidity sensor with mesa structure in which porous silicon layer is used as humidity-sensing material is developed and its humidity sensing properties are measured. This sensor has a structure where two electrodes are set on the up-side of the wafer against the past typical structure having these electrodes on the up and down-side of the wafer. Therefore, the sensor can be fabricated monolithically to be more compatible with the IC process technology, and is possible to detect more correct output capacitance by removing the effect of the parasitic capacitance from the bottom layer and other junctions. To do this, the sensor was fabricated using process such as localized formation of porous silicon, oxidation of porous silicon layer, and etching of oxidized porous silicon layer. From the completed samples, the dependence of capacitance on the relative humidity of 55 to 90% more was measured at room temperature. As the result, the measured capacitance increased monotonously higher at the low frequency of 120 Hz, where the capacitance was observed to increase over 300%.

• Journal of KIISE:Software and Applications
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• v.37 no.8
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• pp.629-640
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• 2010

The exemplar-based inpainting model is widely used to remove objects from natural images and to restore a damaged region. This paper presents a method which improves the performance of the conventional exemplar-based inpainting model by modifying three major parts in the model: data term, confidence term and patch selection. While the conventional data term is calculated using the local gradient, the proposed method uses 16 compass masks to get the global gradient to make the method robust to noise. To overcome the problem that the confidence term gets negligible in the inside of the eliminated region, a method is proposed which makes the confidence term decrease slowly in the eliminated region. The patch selection procedure is modified so that the closer patch has higher weight. Experiments showed that the proposed method produced more natural images and lower reconstruction error than the conventional exemplar-based inpainting.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.05a
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• pp.481-483
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• 2018

Recently, as the demand for electronic communication equipment increases, the importance of image and signal processing is increasing. However, noise is generated in digital signal due to various causes during transmission and reception, lowering equipment reliability and causing malfunction. Particularly, since AWGN may be found in most electronic equipments, AWGN removal is mandatorily performed as a preprocessing phase in various fields, such as image recognition, extraction, and segmentation. In the present paper, an AWGN removal algorithm which considers high frequency components is proposed. Conventional methods show relatively inadequate performance in images with high frequency components. To overcome this problem, proposed is a filter algorithm that add or subtract difference images in the local mask. And to verify performance of the proposed algorithm, PSNR and enlarged images are used to compare with the existing methods.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.26 no.12A
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• pp.2067-2073
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• 2001

Biometric systems are forms of technology that use unique human physical characteristics to automatically identify a person. They have sensors to pick up some physical characteristics, convert them into digital patterns, and compare them with patterns stored for individual identification. However, lip-print recognition has been less developed than recognition of other human physical attributes such as the fingerprint, voice patterns, retinal at blood vessel patterns, or the face. The lip print recognition by a CCD camera has the merit of being linked with other recognition systems such as the retinal/iris eye and the face. A new method using multi-resolution architecture is proposed to recognize a lip print from the pattern kernels. A set of pattern kernels is a function of some local lip print masks. This function converts the information from a lip print into digital data. Recognition in the multi-resolution system is more reliable than recognition in the single-resolution system. The multi-resolution architecture allows us to reduce the false recognition rate from 15% to 4.7%. This paper shows that a lip print is sufficiently used by the measurements of biometric systems.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.2
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• pp.86-94
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• 2010

In this paper, we propose spatially adaptive color demosaicing of noisy Bayer data. When sensor noises are not considered in demosaicing, they may degrade result image. In order to obtain high resolution image, sensor noises are considered in the color demosaicing step. We identify flat, edge and pattern regions at each pixel location to improve the performance of the algorithm and to reduce complexity. Based on the pre-classified regions, the demosaicing of the G channel is performed using the local statistics to reduce the interpolation error. The sensor noise is simultaneously removed by a modified version of non-local mean filter in the green and in the color difference domain. The R and B channels are interpolated easily using fully interpolated and denoised G and color difference values. Experimental results show that the proposed method achieves a significant improvement in terms of visual and numerical criteria, when compared to conventional methods.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.10
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• pp.1955-1960
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• 2016

Currently, with the rapid development in digital era, the image equipment related to multi-media is becoming commercialized. However, in the process of transmitting image data, deterioration occurs due to various causes, and the most representative deterioration is salt and pepper noise. There are many methods of eliminating salt and pepper noise such as SWMF, RSIF, MNRF, which are rather insufficient in eliminating noise in high-density slat and pepper noise environment. Therefore, in order to eliminate salt and pepper noise, this thesis proposes an algorithm by first judging the noise, and when the center pixel value is non-noise, the original pixel is preserved, and when it is noise, the partial mask is subdivided into 4 directions to apply cubic spline interpolation to the direction with most non-noise pixels. Also, for the objective judgement, it was compared to existing methods, and the PSNR(peak signal to nise ratio) was set as the judgement standard.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.05a
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• pp.661-663
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• 2016

Corruption occurs in the process of processing image signal and the corruption changes the pixel value within the image to damage the original information. AWGN(additive white Gaussian noise) is a representative example. For filters to remove AWGN, there are filters such as MF(mean filter), WF(wiener filter), and AWMF(adaptive weighted mean filter). However images processed through standard previous filters lock preservation characteristics in edge areas. Therefore, threshold value is applied for processing on the standard deviation of the local mask in this study and if the standard deviation is smaller than the threshold value, it is not filtered and if the value is bigger than the threshold value, the study suggested an algorithm that processes using weighted value utilizing standard deviation.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.05a
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• pp.343-345
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• 2017

In digital era image processing has been utilized in a variety of media such as TV, camera and smart phone. However, in the process of analyzing, recognizing, and processing image data, deterioration occurs due to various causes and Salt & Pepper noise occurs. Typical methods for removing such noise include SMF, CWMF, and SWMF. However, existing methods have a somewhat poor noise canceling characteristic in Salt & Pepper noise environment. Therefore, in this paper, we propose an algorithm to remove Salt & Pepper noise effectively by using bilinear interpolation method and median filter according to noise density of local mask. And using the PSNR(Peak Signal to Noise Ratio) it compared to the existing methods and their performance in order to determine the performance of the proposed method.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.9
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• pp.2167-2172
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• 2015

Due to the recent progress in information technology, demand for video imaging devices such as displays has grown. In general, images experience deterioration during the process of transmission due to various reasons. Many studies have boon undertaken on ways o reduce such noise. This paper6 suggests an algorithm that makes a judgment on the noise in order to remove the salt & pepper noise and replaces original pixels if they are non-noise while processing noise according to its density. The suggested algorithm shows a high PSNR of 30.49[dB] for Goldhill images that had been damaged of a high density salt & pepper noise(P = 60%), Compared to the exising CWMF, SWMF, and A-TMF, there were improvements by 17.74[dB], 11.52[dB], and 13.76[dB], respectively.