• Journal of Sensor Science and Technology
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• v.8 no.2
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• pp.124-132
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• 1999

In this paper, we propose interband vector quantization of remotely sensed satellite image using edge region compensation. This method classifies each pixel vector considering spectral reflection characteristics of satellite image data. For each class, we perform classified intraband VQ and classified interband VQ to remove intraband and interband redundancies, respectively. In edge region case, edge region is compensated using class information of neighboring blocks and gray value of quantized reference band. Then we perform classified interband VQ to remove interband, redundancy using compensated class information, effectively. Experiments on remotely sensed satellite image show that coding efficiency of the proposed method is better than that of the conventional method.

• ETRI Journal
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• v.32 no.3
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• pp.380-389
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• 2010

This paper presents a new edge-protection algorithm and its very large scale integration (VLSI) architecture for block artifact reduction. Unlike previous approaches using block classification, our algorithm utilizes pixel classification to categorize each pixel into one of two classes, namely smooth region and edge region, which are described by the edge-protection maps. Based on these maps, a two-step adaptive filter which includes offset filtering and edge-preserving filtering is used to remove block artifacts. A pipelined VLSI architecture of the proposed deblocking algorithm for HD video processing is also presented in this paper. A memory-reduced architecture for a block buffer is used to optimize memory usage. The architecture of the proposed deblocking filter is verified on FPGA Cyclone II and implemented using the ANAM 0.25 ${\mu}m$ CMOS cell library. Our experimental results show that our proposed algorithm effectively reduces block artifacts while preserving the details. The PSNR performance of our algorithm using pixel classification is better than that of previous algorithms using block classification.

• Journal of information and communication convergence engineering
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• v.6 no.1
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• pp.80-85
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• 2008

Images are often corrupted by noises during signal acquisition and transmission. Among those noises, additive white Gaussian noise (AWGN) and impulse noise are most representative. For different types of noise have different characters, how to remove them separately from degraded image is one of the most fundamental problems. Thus, a modified image restoration algorithm is proposed in this paper, which can not only remove impulse noise of random values, but also remove the AWGN selectively. The noise detection step is by calculating the intensity difference and the spatial distance between pixels in a mask. To divide two different noises, the method is based on three weighted parameters. And the weighted parameters in the filtering mask depend on spatial distances, positions of impulse noise and standard deviation of AWGN. We also use the peak signal-to-noise ratio (PSNR) to evaluate restoration performance, and simulation results demonstrate that the proposed method performs better than conventional median-type filters, in preserving edge details.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.6A
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• pp.568-574
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• 2002

The main issue of noise reduction of image is how to preserve edge and reduce noise. Usually, The Wiener falter is used for this purpose. But the conventional Wiener filter cannot remove noise well in both edge and smooth region due to the single size estimation window. In addition, it ignores the correlation between pixels. In this paper, we propose a new noise reduction algorithm, in which adaptive estimation window is used according to property of smooth region and edge region. In order to make edge more clear, directional Gaussian mask and directional estimation window combines to the Wiener filter according to direction of edge. From the simulation results, it can be seen that the proposed algorithm showed improves performance in both PSNR arid subjective evaluation

• Proceedings of the KSR Conference
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• 2007.11a
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• pp.872-898
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• 2007

Pantograph sliding plate abrasion auto-detect system, one of the electric rail car auto-detecting devices, is a system that decides how much abrasion and when to replace without an inspector physically looking at the abrasion on the wet plate using machine vision, a cutting-edge technology. This paper covers the cause of deteriorating reliability that affects pantograph wet plate edge detection due to noise added to the video when it rains. In order to remove such noise, problems should be checked through Smoothing, Averaging mask and Median filter using filtering technique and stable edge detection without being affected by noise should be induced in video measurement used in machine vision technology.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.22 no.6
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• pp.148-155
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• 2008

This study presents a process control of the wafer edge exposure (WEE) used in 300[mm] wafer environment. WEE, as a key module of the overall track system (coater and developer) for making patterns on wafer, is a system to expose the UV-ray on the wafer to remove a photo resist around edge of the wafer. It can measure, memorize and control the distance and angles from wafer center to edge. Recently in the 300[mm] semiconductor fabrication, the track system strongly requires that WEE station has a controller with high throughput and accuracy to increase process efficiency. We have designed and developed the controller, and present here a WEE control algorithm and experimental results.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.169-172
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• 2005

Modem SAR interferometry (IFSAR) sensors delivering intensity images and corresponding digital terrain model (DTM) allow for a thorough surface lineament interpretation with the all-weather day-night applicability. In this paper, an automatic linear-feature detection algorithm for high-resolution SAR images acquired in Taiwan is proposed. Methodologies to extract linear features consist of several stages. First, the image denoising techniques are used to remove the speckle noise on the raw image. In this stage, the Lee filter has been chosen because of its superior performance. After denoising, the Coefficient of Variation Detector is performed on the result images for edge enhancements and detection. Dilation and erosion techniques are used to reconnect the fragmented lines. The Hough transform, which is a special case of a more general transform known as Radon transform, is a suitable method for line detection in our analysis. Finally, linear features are extracted from the binary edge image. The last stage contains many substeps such as edge thinning and curve pruning.

• Proceedings of the KIEE Conference
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• 2007.11c
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• pp.191-193
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• 2007

Pantograph sliding plate abrasion auto-detect system, one of the electric rail car auto-detecting devices, is a system that decides how much abrasion and when to replace without an inspector physically looking at the abrasion on the wet plate using machine vision, a cutting-edge technology. This paper covers the cause of deteriorating reliability that affects pantograph wet plate edge detection due to noise added to the video when it rains. In order to remove such noise, problems should be checked through Smoothing, Averaging mask and Median filter using filtering technique and stable edge detection without being affected by noise should be induced in video measurement used in machine vision technology.

• Proceedings of the IEEK Conference
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• 2002.06c
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• pp.231-234
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• 2002

This paper proposes a new approach to extract contour of moving object from compressed video stream. We segment the area of moving object by using motion vector and extract the motion object block from it. And then we describe the connectivity direction of outline moving block, detect the edge related to connectivity direction in the block and finally obtain the contour by connecting the edges. This can divide the moving object only with motion vector and detect the exact contour on the basis of the edge automatically. Also, we can reduce spending time using motion block and remove the noise with directional edge. The experimental results demonstrate the accurate and effective qualify of the proposed method.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.830-833
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• 2009

Deblocking Filter (DF) is newly introduced into H.264/AVC to remove blocky artifacts. It improves the picture quality and the improved picture is set to the frame buffer for motion compensation. As a result, higher coding efficiency is achieved by DF. However, if the original image has heavily-slanted patterns, DF removes the edges to be kept because it is applied only perpendicularly to the block boundaries. In this paper, we propose Edge Adaptive Deblocking Filter (EADF) which is applied not only for the perpendicular but also for several slanted directions to deal with the problem. Simulation results showed us that EADF was especially effective for the sequence "Foreman" with PSNR gain of 0.04 dB.