• Journal of Korea Society of Digital Industry and Information Management
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• v.8 no.3
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• pp.41-48
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• 2012

In this paper, we propose a method of edge detection for noisy image. The proposed method uses a progressive filter for noise reduction and a Sobel operator for edge detection. The progressive filter combines a median filter and a modified rational filter. The proposed method for noise reduction adjusts rational filter direction according to an edge in the image which is obtained by median filtering. Our method effectively attenuates the noise while preserving the image details. Edge detection is performed by a Sobel operator. This operator can be implemented by integer operation and is therefore relatively fast. Our proposed method not only preserves edge, but also reduces noise in uniform region. Thus, edge detection is well performed. Our proposed method could improve results using further developed Sobel operator. Experimental results show that our proposed method has better edge detection with correct positions than those by existing median and rational filtering methods for noisy image.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.49 no.4
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• pp.23-30
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• 2012

This paper proposes an improved steganalysis method to detect the existence of secret message. Firstly, we magnify the small stego noise by multiplying the speckle noise to a given image and then we estimate the denoised image by using the soft thresholding method. Because the noises are not perfectly eliminated, some noises exist in the estimated cover image. If the given image is the cover image, then the remained noise will be very small, but if it is the stego image, the remained noise will be relatively large. The parent-child relationship in the wavelet domain will be slighty broken in the stego image. From this characteristic, we extract the joint statistical moments from the difference image between the given image and the denoised image. Additionally, four statistical moments are extracted from the denoised image for the proposed steganalysis method. All extracted features are used as the input of MLP(multilayer perceptron) classifier. Experimental results show that the proposed scheme outperforms previous methods in terms of detection rates and accuracy.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2018.11a
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• pp.73-76
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• 2018

A Gaussian noise is caused by surrounding environment or channel interference when transmitting image. The noise reduces not only image quality degradation but also high-level image processing performance. The Non-Local Means (NLM) filter finds similarity in the neighboring sets of pixels to remove noise and assigns weights according to similarity. The weighted average is calculated based on the weight. The NLM filter method shows low noise cancellation performance and high complexity in the process of finding the similarity using weight allocation and neighbor set. In order to solve these problems, we propose an algorithm that shows an excellent noise reduction performance by using Summed Square Image (SSI) to reduce the complexity and applying the weighting function based on a cosine Gaussian kernel function. Experimental results demonstrate the effectiveness of the proposed algorithm.

• ETRI Journal
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• v.36 no.3
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• pp.510-513
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• 2014

A Q-band pHEMT image-rejection low-noise amplifier (IR-LNA) is presented using inter-stage tunable resonators. The inter-stage L-C resonators can maximize an image rejection by functioning as inter-stage matching circuits at an operating frequency ($F_{OP}$) and short circuits at an image frequency ($F_{IM}$). In addition, it also brings more wideband image rejection than conventional notch filters. Moreover, tunable varactors in L-C resonators not only compensate for the mismatch of an image frequency induced by the process variation or model error but can also change the image frequency according to a required RF frequency. The implemented pHEMT IR-LNA shows 54.3 dB maximum image rejection ratio (IRR). By changing the varactor bias, the image frequency shifts from 27 GHz to 37 GHz with over 40 dB IRR, a 19.1 dB to 17.6 dB peak gain, and 3.2 dB to 4.3 dB noise figure. To the best of the authors' knowledge, it shows the highest IRR and $F_{IM}/F_{OP}$ of the reported millimeter/quasi-millimeter wave IR-LNAs.

• Journal of KSNVE
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• v.7 no.2
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• pp.255-260
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• 1997

This paper describes 3-dimensional volume array of 4 microphones including a reference microphone which is capable of imaging wideband noise source position in 2-dimensional image plane. The cross correlation function and corresponding imaging function between a reference microphone and other microphone, are derived as a function of noise source position. The magnitude of the imaging function gives noise source mapping in image plane. Since the image plane is selective from a rectangular and a cylindrical plane, noise source position information such as range and bearing relative to the array is identified very much easily. Simulation results for typical source configurations confirms the applicability of the proposed array in noise control field.

• Journal of IKEEE
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• v.23 no.4
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• pp.1465-1468
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• 2019

The image noise improvement algorithm proposed in this paper extracts the boundary line by using the window of the binarized image to detect the gesture motion. Boundary line blurring is prevented by improving Gaussian noise generated during video output. To improve gesture recognition in low-light environments, an image noise enhancement algorithm has been designed to provide an output image close to the base image. Analyzing the experimental results, we found almost 10% improvement in the results compared to the results of the existing Median filter.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.23 no.1
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• pp.27-35
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• 2009

The moving picture blur noise of LCD is measured and the characteristics of it are evaluated. From the results, blur noise is generated only when the sight line moves while pursuing the moving image and blur noise is not generated when the sight line is fixed. In addition, decrease of gray level by the image blur has a linearity and velocity dependence. The blur noise simulator based on this experimental results is developed. From the results of blur noise simulation, the faster the moving speed of image is, the more blur noise has increased and these agree with the results of measurement. In the result of simulating blur noise characteristics by the duty ratio control of backlight, noise is reduced by lowering of the duty ratio. but the blur noise increases if there is in the both of adjacent two frames. Moreover, the case of doubling the frame rate to 120[Hz], decreasing the moving speed of the image by making an new image between the adjacent two frames brings the reduction of blur noise.

• International Journal of Computer Science & Network Security
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• v.21 no.12spc
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• pp.556-564
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• 2021

Numerous spatial and transform-domain-based conventional denoising algorithms struggle to keep critical and minute structural features of the image, especially at high noise levels. Although neural network approaches are effective, they are not always reliable since they demand a large quantity of training data, are computationally complicated, and take a long time to construct the model. A new framework of enhanced hybrid filtering is developed for denoising color images tainted by additive white Gaussian Noise with the goal of reducing algorithmic complexity and improving performance. In the first stage of the proposed approach, the noisy image is refined using a high-dimensional non-local means filter based on Principal Component Analysis, followed by the extraction of the method noise. The wavelet transform and SURE Shrink techniques are used to further culture this method noise. The final denoised image is created by combining the results of these two steps. Experiments were carried out on a set of standard color images corrupted by Gaussian noise with multiple standard deviations. Comparative analysis of empirical outcome indicates that the proposed method outperforms leading-edge denoising strategies in terms of consistency and performance while maintaining the visual quality. This algorithm ensures homogeneous noise reduction, which is almost independent of noise variations. The power of both the spatial and transform domains is harnessed in this multi realm consolidation technique. Rather than processing individual colors, it works directly on the multispectral image. Uses minimal resources and produces superior quality output in the optimal execution time.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.429-431
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• 2019

Noise in image processing has a direct effect on the quality of the image, and adversely affects the processing of the system including algorithms such as image segmentation, edge detection, and image recognition. Therefore, noise reduction plays an important role in the preprocessing process. In this paper, we propose an efficient algorithm to remove noise in high density of Salt and Pepper noise. The proposed algorithm removes noise by gradually expanding the filtering mask according to the density of the noise, and shows excellent noise cancellation performance even in a high density region. In order to evaluate the performance of the proposed algorithm, we compared and analyzed the existing method and the proposed algorithm through simulation.

• Nuclear Engineering and Technology
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• v.54 no.9
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• pp.3380-3389
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• 2022

We evaluated the performance of an improved hybrid median filter (IHMF) applied to X-ray computed tomography (CT) images obtained using a high-resolution photon-counting cadmium zinc telluride (CZT) detector. To study how the proposed approach improves the image quality, we measured the noise levels and the overall CT-image quality. We established a CZT imaging system with a detector length of 5.12 cm and thickness of 0.3 cm and acquired phantom images. To evaluate the efficacy of the proposed filter, we first modeled two conventional median filters. Subsequently, we were able to achieve a normalized noise power spectrum result of ~10^-8 mm², and furthermore, the proposed method improved the contrast-to-noise ratio by a factor of ~1.51 and the coefficient of variation by 1.55 relative to the counterpart values of the no-filter image. In addition, the IHMF exhibited the best performance among the three filters considered as regards the peak signal-to-noise ratio and no-reference-based image-quality evaluation parameters. Thus, our results demonstrate that the IHMF approach provides a superior image performance over conventional median filtering methods when applied to actual CZT X-ray CT images.