• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.154-154
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• 2021

Since the development of Bubble Image Velocimetry (BIV) technique as the complementary technique of Particle Image Velocimetry (PIV), the application of digital imaging technique in the field of hydraulic and coastal engineering increased rapidly. BIV works very well in multi-phase flow (air-water) flows where the PIV technique doesn't. However, the velocity field obtained from BIV technique often resulted in a velocity vector on the outside of the flow (false velocity) since the Field of View (FOV) usually not only cover the air-water flow but also the area outside the flow. In this study, a simple technique of post processing velocity field was developed. This technique works based on the average of the pixel value in the interrogation area. An image of multi-phase flow of wave overtopping was obtained through physical experiment using BIV technique. The velocity calculation was performed based on the similar method in PIV. A velocity masking technique developed in this study then applied to remove the false velocity vector. Result from non-masking, manually removed and auto removed false velocity vector were presented. The masking technique show a similar result as manually removed velocity vector. This method could apply in a large number of velocity field which is could increase the velocity map post-processing time.

• Journal of Biomedical Engineering Research
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• v.6 no.2
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• pp.29-32
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• 1985

We have developed a real time digital subtraction a giographic system(RTDSA) and specified it's performance characteristics. Our RTDSA has large-capacity frame memories and a post-processing computer which enables various advanced digital image processing techniques.

• Investigative Magnetic Resonance Imaging
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• v.24 no.1
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• pp.1-20
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• 2020

This document is the third part of the guidelines for the interpretation and post-processing of cardiac magnetic resonance (CMR) studies. These consensus recommendations have been developed by a Consensus Committee of the Korean Society of Cardiovascular Imaging (KOSCI) to standardize the requirements for image interpretation and post-processing of CMR. This third part of the recommendations describes tissue characterization modules, including perfusion, late gadolinium enhancement, and T1- and T2 mapping. Additionally, this document provides guidance for visual and quantitative assessment, consisting of "What-to-See," "How-To," and common pitfalls for the analysis of each module. The Consensus Committee hopes that this document will contribute to the standardization of image interpretation and post-processing of CMR studies.

• IEMEK Journal of Embedded Systems and Applications
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• v.16 no.1
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• pp.17-27
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• 2021

In this paper, we develop a galaxy image classification method based on hand-crafted features and machine learning techniques. Additionally, we provide an empirical analysis to reveal which combination of the techniques is effective for galaxy image classification. To achieve this, we developed a framework which consists of four modules such as preprocessing, feature extraction, feature post-processing, and classification. Finally, we found that the best technique for galaxy image classification is a method to use a median filter, ORB vector features and a voting classifier based on RBF SVM, random forest and logistic regression. The final method is efficient so we believe that it is applicable to embedded environments.

• Proceedings of the IEEK Conference
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• 2005.11a
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• pp.427-430
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• 2005

In this paper, we propose a new post-processing method, based on the theory of the projection onto convex sets (POCS) to reduce the blocking artifacts in decoded images. We propose a new smoothness constraint set (SCS) and its projection operator in the wavelet transform (WT) domain to remove unnecessary high-frequency components caused by blocking artifacts. We also propose a new method to find and preserve the original high frequency components of the image edge. Experimental results show that the proposed method can not only achieve a significantly enhanced subjective quality, but also have the PSNR improvement in the output image.

• International Journal of Contents
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• v.11 no.3
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• pp.7-13
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• 2015

One of the biggest problems of skeletonization is the occurrence of distortions at the junction point of the final binary image. At the junction area, a single point usually becomes a small stroke, and the corresponding trajectory task, as well as the OCR, consequently becomes more complicated. We therefore propose an adaptive post-processing method that uses an adaptive threshold technique to correct the distortions. Our proposed method transforms the distorted segments into a single point so that they are as similar to the original image as possible, and this improves the static handwriting images after the skeletonization process. Further, we attained promising results regarding the usage of the enhanced skeletonized images in other applications, thereby proving the expediency and efficiency of the proposed method.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.18
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• pp.8351-8358
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• 2016

Electronic cleansing is an image post processing technique in which the tagged colonic content is subtracted from colon using CTC images. There are post processing artefacts, like: 1) soft tissue degradation; 2) incomplete cleansing; 3) misclassification of polyp due to pseudo enhanced voxels; and 4) pseudo soft tissue structures. The objective of the study was to subtract the tagged colonic content without losing the soft tissue structures. This paper proposes a novel adaptive method to solve the first three problems using a multi-step algorithm. It uses a new edge model-based method which involves colon segmentation, priori information of Hounsfield units (HU) of different colonic contents at specific tube voltages, subtracting the tagging materials, restoring the soft tissue structures based on selective HU, removing boundary between air-contrast, and applying a filter to clean minute particles due to improperly tagged endoluminal fluids which appear as noise. The main finding of the study was submerged soft tissue structures were absolutely preserved and the pseudo enhanced intensities were corrected without any artifact. The method was implemented with multithreading for parallel processing in a high performance computer. The technique was applied on a fecal tagged dataset (30 patients) where the tagging agent was not completely removed from colon. The results were then qualitatively validated by radiologists for any image processing artifacts.

• Journal of ILASS-Korea
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• v.26 no.3
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• pp.142-148
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• 2021

The objective of this study is to analyze the basic flame behavior characteristics using the single fuel droplet combustion of diesel, palm-based biodiesel, and canola-based biodiesel. The results were compared and analyzed through the post processed image, which was applied the threshold level for removing noise in the raw image. The raw image was taken by a high-speed camera during the entire combustion process. At the same time, the maximum flame length, which was measured by the application code of the MATLAB program, the ignition delay, and the combustion period were compared and analyzed.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.7
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• pp.1907-1928
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• 2024

In recent years, multi-focus image fusion has emerged as a prominent area of research, with transformers gaining recognition in the field of image processing. Current approaches encounter challenges such as boundary artifacts, loss of detailed information, and inaccurate localization of focused regions, leading to suboptimal fusion outcomes necessitating subsequent post-processing interventions. To address these issues, this paper introduces a novel multi-focus image fusion technique leveraging the Swin Transformer architecture. This method integrates a frequency layer utilizing Wavelet Transform, enhancing performance in comparison to conventional Swin Transformer configurations. Additionally, to mitigate the deficiency of local detail information within the attention mechanism, Convolutional Neural Networks (CNN) are incorporated to enhance region recognition accuracy. Comparative evaluations of various fusion methods across three datasets were conducted in the paper. The experimental findings demonstrate that the proposed model outperformed existing techniques, yielding superior quality in the resultant fused images.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.8B
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• pp.1480-1489
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• 1999

In this paper, we propose a new post-processing method which can solve a problem of MSDS(Mean Squared Difference of Slope) method. Using that method the blocking artifacts can significantly be reduced without any restriction, which is a major drawback of block-based DCT compression method. In this approach, the OSLD(Overlapped Sub-Laplacian Distribution) of dequantized block boundary pixel difference values is defined and used to categorize each block of an image into one of four types. Those types are also classified into one of two classes: an edge and a non-edge classes. A slope across the block boundary is used to quantify discontinuity of the image. If an absolute estimated quantization error value of a DCT coefficient is greater than the corresponding quantization step size, it is saturated to the step size in the edge class. The proposed post-processing method can improve not only the PSNR value up to 0.1~O.3 dB but visual quality without any constraints determined by ad-hoc manner.