• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.6
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• pp.79-84
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• 2015

In a distribution of digital image, there is a serious problem that is a distribution of the altered image by a forger. For the problem solution, this paper proposes a median filtering (MF) image forensic decision algorithm using a feature vector according to the pixel value's gradients. In the proposed algorithm, AR (Autoregressive) coefficients are computed from pixel value' gradients of original image then 1th~6th order coefficients to be six feature vector. And the reconstructed image is produced by the solution of Poisson's equation with the gradients. From the difference image between original and its reconstructed image, four feature vector (Average value, Max. value and the coordinate i,j of Max. value) is extracted. Subsequently, Two kinds of the feature vector combined to 10 Dim. feature vector that is used in the learning of a SVM (Support Vector Machine) classification for MF (Median Filtering) detector of the altered image. On the proposed algorithm of the median filtering detection, compare to MFR (Median Filter Residual) scheme that had the same 10 Dim. feature vectors, the performance is excellent at Unaltered, Averaging filtering ($3{\times}3$) and JPEG (QF=90) images, and less at Gaussian filtering ($3{\times}3$) image. However, in the measured performances of all items, AUC (Area Under Curve) by the sensitivity and 1-specificity is approached to 1. Thus, it is confirmed that the grade evaluation of the proposed algorithm is 'Excellent (A)'.

• Journal of Korea Multimedia Society
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• v.15 no.12
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• pp.1417-1429
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• 2012

In neuroscientific research, image segmentation is one of the most important processes. The morphology of axons plays an important role for researchers seeking to understand axonal functions and connectivity. In this study, we evaluated the level set segmentation method for neuronal axons in a Brainbow confocal microscopy image. We first obtained a reconstructed image on an x-z plane. Then, for preprocessing, we also applied two methods: anisotropic diffusion filtering and bilateral filtering. Finally, we performed image segmentation using the level set method with three different approaches. The accuracy of segmentation for each case was evaluated in diverse ways. In our experiment, the combination of bilateral filtering with the level set method provided the best result. Consequently, we confirmed reasonable results with our approach; we believe that our method has great potential if successfully combined with other research findings.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.505-508
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• 2005

Wavelet scheme can be applied to the various remote sensing problems: conventional multi-resolution image analysis, compression of large image sets, fusion of heterogeneous sensor image and segmentation of features. In this study, we attempted wavelet-based filtering and its analysis. Traditionally, statistical methods and adaptive filter are used to manipulate noises in the image processing procedure. While we tried to filter random noise from optical image and radar image using Discrete Wavelet Transform (DW1) and Stationary Wavelet Transform (SW1) and compared with existing methods such as median filter and adaptive filter. In result, SWT preserved boundaries and reduced noises most effectively. If appropriate thresholds are used, wavelet filtering will be applied to detect road boundaries, buildings, cars and other complex features from high-resolution imagery in an urban environment as well as noise filtering

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.5
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• pp.42-47
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• 2017

In the distribution of digital image, the median filtering is used for a forgery. This paper proposed the algorithm of a image forensics detection for the classification of median filtering. For the solution of this grave problem, the feature vector is composed of 42-Dim. The detected quantity 32, 64 and 128 of forgery image edges, respectively, which are processed by the Hough transform, then it extracted from the start-end point coordinates of the Hough Lines. Also, the Hough Peaks of the Angle-Distance plane are extracted. Subsequently, both of the feature vectors are composed of the proposed scheme. The defined 42-Dim. feature vector is trained in SVM (Support Vector Machine) classifier for the MF classification of the forged images. The experimental results of the proposed MF detection algorithm is compared between the 10-Dim. MFR and the 686-Dim. SPAM. It confirmed that the MF forensic classification ratio of the evaluated performance is 99% above with the whole test image types: the unaltered, the average filtering ($3{\times}3$), the JPEG (QF=90 and 70)) compression, the Gaussian filtered ($3{\times}3$ and $5{\times}5$) images, respectively.

• 전자공학회논문지 IE
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• v.49 no.2
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• pp.75-81
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• 2012

In this paper, restoration methods were applied to restore analog medicine images with an aged image added and then blurred by noises. To restore the aged image blurred by the blurring function and added by noises, it was applied to the restoration methods which are inverse filtering and wiener filtering which are linear restoration techniques and Lucy-Richardson's algorithm which is nonlinear restoration technique. Moreover, ROC curve, a subjective evaluation method, was applied to evaluate the image quality of the restoration image. The wiener filtering using the ratio of constants acquired better image than the inverse filtering, but both of them couldn't improve ability to make a diagnosis. The restoration image applied to Lucy-Richardson algorithm was the best performance of the applied techniques and its sensitivity and specitivity were improved by 15[%] as much performance as the original aged image.

• Journal of the Korean Society of Radiology
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• v.2 no.4
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• pp.33-40
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• 2008

Images acquired by a digital X-ray imaging system are inherently degraded due to system degradation process and additive noise sources. The system degradation in image quality is typically described as the system response function characterized by the modulation transfer function (MTF) and the noise term described as the noise power spectrum (NPS). In this case, we can restore the blur image as close as possible to the original image by using modified filtering designed for digital imaging system, as we know more precisely about the MTF and the NPS. In this paper, by performing simulation, we tried to restore blurred images taken from a digital X-ray imaging system based upon conventional filtering techniques such as a direct-inverse filtering, limited-inverse filtering, or a Wiener filtering, and evaluated the characteristics of the image restoration.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.6
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• pp.1303-1310
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• 2021

We propose an edge-preserving transmission estimation by comparing the patch-based dark channel and the pixel-based dark channel near the edge, in order to improve the quality of outdoor images deteriorated by conditions such as fog and smog. Moreover, we propose a refinement that applies the Guided Image Filtering (GIF), a kind of edge-preserving smoothing filtering methods, to edges using Laplacian operation for natural restoration of image objects and backgrounds, so that we can dehaze a single image and improve the visibility effectively. Experimental results carried out on various outdoor hazy images that show the proposed method has less computational complexity than the conventional methods, while reducing distortion such as halo effect, and showing excellent dehazing performance. In It can be confirmed that the proposed method can be applied to various fields including devices requiring real-time performance.

• Journal of information and communication convergence engineering
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• v.7 no.4
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• pp.535-538
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• 2009

Speckle noise reduction for ultrasound CT image using morphological adaptive median filtering based on edge preservation is presented in this paper. Speckle noise is multiplicative feature and causes ultrasound image to degrade widely from transducer. An input image is classified into edge region and homogeneous region in preprocessing. The speckle is reduced by morphological operation on the 2D gray scale by using convolution and correlation, and edges are preserved. The adaptive median is processed to reduce an impulse noise to preserve edges. As the result, MAM of the proposed method enhances the image to about 10% in comparison with Winner filter by Edge Preservation Index and PSNR, and 10% to only adaptive median filtering.

• Journal of Electrical Engineering and Technology
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• v.10 no.5
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• pp.2197-2204
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• 2015

In recent years, medical image diagnosis has growing significant momentous in the medicinal field. Brain and lung image of patient are distorted with salt and pepper noise is caused by moving the head and chest during scanning process of patients. Reconstruction of these images is a most significant field of diagnostic evaluation and is produced clearly through techniques such as linear or non-linear filtering. However, restored images are produced with smaller amount of noise reduction in the presence of huge magnitude of salt and pepper noises. To eliminate the high density of salt and pepper noises from the reproduction of images, a new efficient fuzzy based median filtering algorithm with a moderate elapsed time is proposed in this paper. Reproduction image results show enhanced performance for the proposed algorithm over other available noise reduction filtering techniques in terms of peak signal -to -noise ratio (PSNR), mean square error (MSE), root mean square error (RMSE), mean absolute error (MAE), image enhancement factor (IMF) and structural similarity (SSIM) value when tested on different medical images like magnetic resonance imaging (MRI) and computer tomography (CT) scan brain image and CT scan lung image. The introduced algorithm is switching filter that recognize the noise pixels and then corrects them by using median filter with fuzzy two-sided π- membership function for extracting the local information.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.24 no.10
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• pp.1-4
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• 2010

It is proposed the basic filtering method to remove bias and conjugate image in incoherent hologram. To demonstrate the feasibility of the proposed method, the image reconstruction of incoherent hologram is presented.