• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.06a
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• pp.209-212
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• 2007

Digital images are corrupted by noises, during signal acquisition and transmission. Amount those noises, additive white Gaussian noise (AWGN) and impulse noise are most representative. The conventional image restoration algorithms are mostly taken in simple noise environment, but they didn't perform very well in tempter noises environment. So a modified image restoration algorithm, which can remove complex noises by using the intensity differences and spatial distances between center pixel and its neighbor pixels as parameters, is proposed in this paper. Simulation results demonstrate that the proposed algorithm can't only remove AWGN and impulse noise separately, but also performs well in preserving details of images as edge.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.798-801
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• 2014

Nowadays, the demand for multimedia services has grown with the rapid evolution in the digital era. But due to external causes in the process of processing, transmitting and storing image data, the images are damaged. One of the major causes of such damage is known to be noise. Some of the most commonly used methods for removing noise are CWMF(center weighted median filter), A-TMF(alpha-trimmed mean filter) and AWMF(adaptive weighted median filter). However, these filters all leave a bit to be desired in removing noise in a complex noise environment. Therefore this paper suggest an image restoration filter algorithm that first judges the noise and sets a adjustment weight based on the median value and distance of the mask to remove the complex noise. For an objective analysis, the results were compared against existing methods and the PSNR(peak signal to noise ratio) was used as a reference.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.9
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• pp.2265-2271
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• 2014

In modern society digital equipments that are related with various hardware and software are popularized, and digital images are widely applied in the field of production and scientific research. In general, however, images are degraded by the noise in the process of transmission and storage. In this paper, to reduce the influence of mixed noises, the algorithm in which noises in the space area are classified into impulse noise and Gaussian noise and this is processed by applying weighted value, while that is processed by modified nonlinear filter is proposed. And the excellence of the proposed algorithm is judged by PSNR(peak signal to noise ratio).

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.43 no.2 s.308
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• pp.63-71
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• 2006

Denoising and reconstruction of color images are extensively studied in the field of computer vision and image processing. Especially, denoising and reconstruction of color face images are more difficult than those of natural images because of the structural characteristics of human faces as well as the subtleties of color interactions. In this paper, we propose a denoising method based on PCA reconstruction for removing complex color noise on human faces, which is not easy to remove by using vectorial color filters. The proposed method is composed of the following five steps: training of canonical eigenface space using PCA, automatic extraction of facial features using active appearance model, relishing of reconstructed color image using bilateral filter, extraction of noise regions using the variance of training data, and reconstruction using partial information of input images (except the noise regions) and blending of the reconstructed image with the original image. Experimental results show that the proposed denoising method maintains the structural characteristics of input faces, while efficiently removing complex color noise.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.12
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• pp.2701-2706
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• 2009

There are Impulse noise and AWGN in a general image processing. Various methods have been proposed to remove these noises. Well-known filters are Mean, Min-max and Median filter and these show different characteristics depending on the noises. When Impulse noise and AWGN are in superposition environment, single filter doesn't remove noises well. Therefore in this paper, we suggested a switching filter using a probability of noise to restore images in this environment. And we compared a filter with conventional method through simulations.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.11
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• pp.2717-2723
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• 2015

Recently, digital image processing is being applied in various areas of broadcasting, communication, computer graphic and medical science. But, degradation of images occurs in the process of digital image acquisition, processing and transmission. Therefore, in order to remove the mixed noise, this paper suggested the image restoration algorithm to process salt and pepper noise with weighted filters according to 4 direction pixel changes after judging the noise and to process AWGN with weighted filters which have individually different characteristics. Regarding the processed results by applying Boat images which were corrupted by salt and pepper noise(P=40%), suggested algorithm showed the improvement by 1.33[dB], 1.41[dB], 0.51[dB] respectively compared with the existing CWMF, AWMF, MMF.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.05a
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• pp.397-400
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• 2016

In digital images, the addition due to noise occurs in the process of obtaining, saving, and transmitting. For examples of noise, there are salt and pepper noise, Gaussian noise, and composition noise where various noises are mixed. Existing filters have insufficient noise removal characteristics because it uses single filters in composite noise environment. Therefore the study suggested a switching filter that processes with special weighted value and median filter according to local mask salt and pepper noise density when central pixel is damaged by salt and pepper noise, and processes by applying weighted values differently according to standard deviation of local mask when damaged by Gaussian noise.

• The Journal of the Acoustical Society of Korea
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• v.15 no.4
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• pp.70-76
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• 1996

In the case of an image corrupted with mixed noise, conventional MMSE filter can not remove such a mixed noise properly, because the impulse moise cause a certain bias of the minimum mean-square error estimate at regions close to outliers. In this paper, we proposed the new method or removal of mixed noise by combining MMSE filtering structure with local multi-windowing method according to directions and with ranked-order method. As a result, the improvement of the image quality with the proposed was obtained between about 9.7 and 35.2 times in the sense of NMSE(normalized mean square errors) evaluation than that of MMSE filter. Also, we could obtain the enhanced image in the mixed noisy image from visual and quantitative aspect.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.3
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• pp.254-260
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• 2019

Recently, the importance of signal processing has become gradually significant, as the frequency of video media increases in various fields. However, numerous kinds of noise generated in the transmission and reception processes can possibly affect the signal information, and the noise removal is for that reason essential as a preprocessing step. In this paper, we propose an algorithm to remove the mixed noise which is composed of impulse noise and AWGN. This algorithm is used for image restoration by noise judgment for efficient noise removal in a complex noise environment, and the noise is removed by considering spatial characteristics and pixel variations. Simulation results show that unlike existing methods, the algorithm has excellent noise cancellation characteristics by minimizing both noise effects and consequently eliminating the mixed noise; for objective judgment, we compared and analyzed the data using PSNR and profile.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.10
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• pp.1284-1289
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• 2016

Recently, digital image processing is applied a lot to the broadcasting, communication, computer graphic, and medical sectors. It generates noise when data is transmitted. There are many kinds of noises that add to the image such as salt and pepper noise, AWGN, and complex noise. Thus, this study divides the corrupted image into four4 areas and estimates the types of noises each pixel, and this study suggested a switching filter that separates the estimated into salt and pepper noise and AWGN. In the case that center pixel of local mask is corrupted by salt and pepper noise, it used a histogram probability weighting of subdivided area. Also, in case that it is corrupted by AWGN, algorithm that is applied to with different weights given for the distribution of each area with using subdivided area's distribution was suggested. For an objective comparison and conclusion, this study used PSNR and compared to existing methods.