• Korean Journal of Remote Sensing
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• v.23 no.4
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• pp.273-285
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• 2007

Most stereo matching methods use intensity values in small image patches to measure the correspondence between two points. If the noisy pixels are used in computing the corresponding point, the matching performance becomes low. For this reason, the noise plays a critical role in determining the matching performance. In this paper, we propose a method for combining intensity and edge filters robust to the noise in order to improve the performance of stereo matching using high resolution satellite imagery. We used intensity filters such as Mean, Median, Midpoint and Gaussian filter and edge filters such as Gradient, Roberts, Prewitt, Sobel and Laplacian filter. To evaluate the performance of intensity and edge filters, experiments were carried out on both synthetic images and satellite images with uniform or gaussian noise. Then each filter was ranked based on its performance. Among the intensity and edge filters, Median and Sobel filter showed best performance while Midpoint and Laplacian filter showed worst result. We used Ikonos satellite stereo imagery in the experiments and the matching method using Median and Sobel filter showed better matching results than other filter combinations.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.2
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• pp.202-207
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• 2021

One of the most important tasks in image processing is noise filtering. Noise removal in image is a difficult task due to many reasons such as nonstationary sequences and corrupted by various types of noise. Human's visual perception is heavily based on the edge information. Thus, noise filtering must preserve edges. To remove the noise, we usually use the square-shaped median filter. They possess mathematical simplicity but have the disadvantages that blur the edges. In this paper we consider a new technique for image restoration using a weighted octagonal median filter. The technique consists of simple hypothesis test for edge detection, and we use the weighted octagonal-shaped moving window. The new technique is applied to noise corrupted image and experimental results are compared to the results of the square-shaped median filter and the cross-shaped median filter.

• Journal of IKEEE
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• v.24 no.2
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• pp.507-513
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• 2020

The median filter that is used in various fields requiring image processing converts to a median value of pixels belonging to a radius r for all pixels in the image of n×m size. For 8-bit depth images, an O(nm) time algorithm exists but for over 16-bit depth images, there is an O(nmlog²r) time algorithm of Gil and Werman. In this paper, we propose an efficient median filter algorithm that works for more than 16-bit depth images. The time complexity of our algorithm is the same as that of Gil and Werman, but theoretical analysis and experimental results show that ours is efficient than above two times.

• 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.

• The Korean Journal of Applied Statistics
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• v.23 no.1
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• pp.151-165
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• 2010

Images are often corrupted by impulse noise due to a noise sensor or channel transmission errors. The filter based on SVM(Support Vector Machine) and the improved adaptive median filtering is proposed to preserve image details while suppressing impulse noise for image restoration. Our approach uses an SVM impulse detector to judge whether the input pixel is noise. If a pixel is detected as a noisy pixel, the improved adaptive median filter is used to replace it. To demonstrate the performance of the proposed filter, extensive simulation experiments have been conducted under both salt-and-pepper and random-valued impulse noise models to compare our method with many other well known filters in the qualitative measure and quantitative measures such as PSNR and MAE. Experimental results indicate that the proposed filter performs significantly better than many other existing filters.

• Journal of the Korea Computer Industry Society
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• v.3 no.3
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• pp.321-330
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• 2002

A 2-D median filter has many applications in various image and video signal processing areas. The rapid development in VLSI technology makes it possible to implement a real-time or near real-time 2-D median filter with reasonable cost. For the efficient VLSI implementation, the algorithm should have characteristics such as small memory requirements, regular computations, and local data transfers. This paper presents an architecture of the real-time two-dimensional separable median filter which has appropriate characteristics for the VLSI implementation. For the efficient two-dimensional median filter, a separable two-dimensional median filtering structure and a bit-sliced pipelined median searching algorithm are used. A behavioral simulator is implemented with C language and used for the analysis of the presented architecture.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.05a
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• pp.807-810
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• 2013

In this paper, a new technique for image enhancement using weighted cross-shaped median filter with edge-detection algorithm is proposed. It consists of simple hypothesis test for edge-detection, and makes use of the cross-shaped moving window. This method is applied to noise corrupted image and its results are compared with those of median filters. As for the experimental result, method of weighted cross-shaped median filter is superior to other median filters.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.10a
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• pp.1006-1009
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• 2013

In this paper, a new technique for image enhancement using cross-shaped median filter with edge-detection algorithm is proposed. It consists of simple hypothesis test for edge-detection, and makes use of the cross-shaped window. This method is applied to noise corrupted image and its results are compared with those of median filters. As for the experimental result, method of cross-shaped median filter is superior to other median filters.

• Journal of Korea Society of Digital Industry and Information Management
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• v.4 no.2
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• pp.75-80
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• 2008

The impulse noise is very common and typical noise in the digital image. Many methods are invented in order to remove the impulse noise since the development of Digital Image Processing. For example, the median filter has been used for removing the impulse noise. In this paper, we try to remove the impulse noise using wavelet transformation in the wavelet-transformed detail areas. We also compare the algorithm with median filter with the visual and numerical methods. The result using the algorithm in this paper was much better than the median filter in both removing the noise and keeping the edges. The proposed algorithm needs more calculating time but has more advantages than the median filter has.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.11
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• pp.2715-2720
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• 2014

Median filtering is very effective to remove impulse type noises, so it has been widely used in many signal processing applications. However, due to the time complexity of its non-linearity, median filtering is often used using a small filter window size. A lot of work has been done on devising fast median filtering algorithms, but most of them can be efficiently applied to input data with finite integer values like images. Little work has been carried out on fast 2-d median filtering algorithms that can deal with real-valued 2-d data. In this paper, a fast and simple median 2-d filter is presented, and its performance is compared with the Matlab's 2-d median filter and a heap-based 2-d median filter. The proposed algorithm is shown to be much faster than the Matlab's 2-d median filter and consistently faster than the heap-based algorithm that is much more complicated than the proposed one. Also, a more efficient median filtering scheme for 2-d real valued data with a finite range of values is presented that uses higher-bit integer 2-d median filtering with negligible quantization errors.