• Journal of the Korea Society of Computer and Information
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• v.29 no.7
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• pp.41-51
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• 2024

In this paper, we explore the enhancement of target detection accuracy in the guided weapon using deep learning object detection on infrared (IR) images. Due to the characteristics of IR images being influenced by factors such as time and temperature, it's crucial to ensure a consistent representation of object features in various environments when training the model. A simple way to address this is by emphasizing the features of target objects and reducing noise within the infrared images through appropriate pre-processing techniques. However, in previous studies, there has not been sufficient discussion on pre-processing methods in learning deep learning models based on infrared images. In this paper, we aim to investigate the impact of image pre-processing techniques on infrared image-based training for object detection. To achieve this, we analyze the pre-processing results on infrared images that utilized global or local information from the video and the image. In addition, in order to confirm the impact of images converted by each pre-processing technique on object detector training, we learn the YOLOX target detector for images processed by various pre-processing methods and analyze them. In particular, the results of the experiments using the CLAHE (Contrast Limited Adaptive Histogram Equalization) shows the highest detection accuracy with a mean average precision (mAP) of 81.9%.

• Journal of the Korean Society of Radiology
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• v.84 no.1
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• pp.240-252
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• 2023

Purpose To assess the effect of deep learning image reconstruction (DLIR) for head CT in pediatric patients. Materials and Methods We collected 126 pediatric head CT images, which were reconstructed using filtered back projection, iterative reconstruction using adaptive statistical iterative reconstruction (ASiR)-V, and all three levels of DLIR (TrueFidelity; GE Healthcare). Each image set group was divided into four subgroups according to the patients' ages. Clinical and dose-related data were reviewed. Quantitative parameters, including the signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR), and qualitative parameters, including noise, gray matter-white matter (GM-WM) differentiation, sharpness, artifact, acceptability, and unfamiliar texture change were evaluated and compared. Results The SNR and CNR of each level in each age group increased among strength levels of DLIR. High-level DLIR showed a significantly improved SNR and CNR (p < 0.05). Sequential reduction of noise, improvement of GM-WM differentiation, and improvement of sharpness was noted among strength levels of DLIR. Those of high-level DLIR showed a similar value as that with ASiR-V. Artifact and acceptability did not show a significant difference among the adapted levels of DLIR. Conclusion Adaptation of high-level DLIR for the pediatric head CT can significantly reduce image noise. Modification is needed while processing artifacts.

• Journal of IKEEE
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• v.13 no.2
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• pp.224-231
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• 2009

Unsharp masking is a popular image enhancement technique used to sharpen an image appearance in gray images. However, the conventional unsharp making techniques amplify the noise and easily cause overshoot artifacts. Moreover, the unsharp masking tends to introduce color distortion when it is applied to the each color component independently. To solve these problems, we propose a novel unsharp masking technique based on human visual system and vector projection. The proposed algorithm consists of two steps. First, the proposed algorithm controls the level of sharpening by exploiting the characteristics of the human visual system and contrast region. Then the vector projection is applied to remove the color distortion. Experiment results show that our proposed algorithm successfully produces sharpened images that are free of noise and color distortion commonly found in the conventional unsharp masking algorithms.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.4
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• pp.1594-1617
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• 2018

In this paper, we consider a spectrum access scenario which consists of two groups of users, namely Primary Users (PUs) and Secondary Users (SUs) in Cooperative Cognitive Radio Networks (CCRNs). SUs cooperatively relay PUs messages based on Amplify-and-Forward (AF) and Decode-and-Forward (DF) cooperative techniques, in exchange for accessing some of the spectrum for their secondary communications. From the literatures, we found that the Conventional Distributed Algorithm (CDA) and Pragmatic Distributed Algorithm (PDA) aim to maximize the PU sum-rate resulting in a lower sum-rate for the SU. In this contribution, we have investigated a suit of distributed matching algorithms. More specifically, we investigated SU-based CDA (CDA-SU) and SU-based PDA (PDA-SU) that maximize the SU sum-rate. We have also proposed the All User-based PDA (PDA-ALL), for maximizing the sum-rates of both PU and SU groups. A comparative study of CDA, PDA, CDA-SU, PDA-SU and PDA-ALL is conducted, and the strength of each scheme is highlighted. Different schemes may be suitable for different applications. All schemes are investigated under the idealistic scenario involving perfect coding and perfect modulation, as well as under practical scenario involving actual coding and actual modulation. Explicitly, our practical scenario considers the adaptive coded modulation based DF schemes for transmission flexibility and efficiency. More specifically, we have considered the Self-Concatenated Convolutional Code (SECCC), which exhibits low complexity, since it invokes only a single encoder and a single decoder. Furthermore, puncturing has been employed for enhancing the bandwidth efficiency of SECCC. As another enhancement, physical layer security has been applied to our system by introducing a unique Advanced Encryption Standard (AES) based puncturing to our SECCC scheme.

• Journal of Broadcast Engineering
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• v.20 no.2
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• pp.238-247
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• 2015

We develop the signal processing method for adaptive implementing direction of signal and the frequency sensitivity of human visual system(HVS). Existing multibnad energy scaling method makes ringing artifact because it does not consider signal direction. To solve this problem, we use block gradient for signal direction in addition to existing method. And we use the fact that frequency component of signal is more sensitive than value of signal over human eyes. we enhance the signal according to contrast sensitivity function(CSF) which is the model of frequency sensitivity of human eye. Compared that the existing analysis models only improve the efficiencies in the existing systems, the developed method can process the image signals to be more desirable and suitable to HVS.

• Journal of Broadcast Engineering
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• v.20 no.1
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• pp.40-47
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• 2015

This paper discusses QoS enhancement in the Best-effort services of the service plan provided by MPEG Media Transport (MMT) systems for video streaming applications. Among MMT services, i.e. per-flow, per-class, and best-effort services, the server does not provide guaranteed bandwidth for the best-effort service only. Therefore, in the best-effort services, a bandwidth access priority is defined for various services, where the lowest priority is assigned to the low-level video services. To alleviate the issue of bandwidth limitation in the best-effort services, this paper investigates transmission of low-resolution video with low bitrate and up-sampling. Our experimental results prove the superiority of the proposed method in terms of delivered video quality.

• Journal of Broadcast Engineering
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• v.10 no.4 s.29
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• pp.632-642
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• 2005

This paper presents a new vertex selection scheme for the polygon-based contour approximation. In the proposed method, the entire contour is partitioned into partial segments and they are approximated adaptively with variable accuracy. The approximation accuracy of each segment is controlled based on its relative significance. By computing the relative significance with the texture degradation in the approximation error region, the visual quality enhancement in the reconstructed frames can be achieved under the same amount of the contour data. For this purpose, a decision rule for $d_{max}$ is derived based on inter-region contrasts. In addition, an adaptive vertex selection method using the derived rule is proposed. Experimental results are presented to show the superiority of the proposed method over conventional methods.

• Journal of The Korean Society of Grassland and Forage Science
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• v.38 no.3
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• pp.190-195
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• 2018

Cold, salt and heat are the most critical factors that restrict full genetic potential, growth and development of crops globally. However, clarification of genes expression and regulation is a fundamental approach to understanding the adaptive response of plants under unfavorable environments. In this study, we applied an annealing control primer (ACP) based on the GeneFishing approach to identify differentially expressed genes (DEGs) in Italian ryegrass (cv. Kowinearly) leaves under cold, salt and heat stresses. Two-week-old seedlings were exposed to cold ($4^{\circ}C$), salt (NaCl 200 mM) and heat ($42^{\circ}C$) treatments for six hours. A total 8 differentially expressed genes were isolated from ryegrass leaves. These genes were sequenced then identified and validated using the National Center for Biotechnology Information (NCBI) database. We identified several promising genes encoding light harvesting chlorophyll a/b binding protein, alpha-glactosidase b, chromosome 3B, elongation factor 1-alpha, FLbaf106f03, Lolium multiflorum plastid, complete genome, translation initiation factor SUI1, and glyceraldehyde-3-phosphate dehydrogenase. These genes were potentially involved in photosynthesis, plant development, protein synthesis and abiotic stress tolerance in plants. However, this study provides new insight regarding molecular information about several genes in response to multiple abiotic stresses. Additionally, these genes may be useful for enhancement of abiotic stress tolerance in fodder crops as well a crop improvement under unfavorable environmental conditions.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.4
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• pp.494-499
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• 2012

In this paper, a new method for detecting various objects that can be risks to safety navigation in sea environment is proposed. By analysing Infrared(IR) images obtained from various sea environments, we could find out that object regions include both horizontal and vertical direction edges while background regions of sea surface mainly include vertical direction edges. Therefore, we present an approach to detecting object regions considering horizontal and vertical edges. To this end, in the first step, image enhancement is performed by suppressing noises such as sea glint and complex clutters using a statistical filter. In the second step, a horizontal edge map and a vertical edge map are generated by 1-D Discrete Cosine Transform technique. Then, a combined map integrating the horizontal and the vertical edge maps is generated. In the third step, candidate object regions are detected by a adaptive thresholding method. Finally, exact object regions are extracted by eliminating background and clutter regions based on morphological operation.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.3
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• pp.113-121
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• 2013

In this paper, we propose a sub-pixel rendering algorithm using learning-based 2D FIR filters. The proposed algorithm consists of two stages: the learning and synthesis stages. At the learning stage, we produce the low-resolution synthesis information derived from a sufficient number of high/low resolution block pairs, and store the synthesis information into a so-called dictionary. At the synthesis stage, the best candidate block corresponding to each input high-resolution block is found in the dictionary. Next, we can finally obtain the low-resolution image by synthesizing the low-resolution block using the selected 2D FIR filter on a sub-pixel basis. On the other hand, we additionally enhance the sharpness of the output image by using pre-emphasis considering RGB stripe pattern of display. The simulation results show that the proposed algorithm can provide significantly sharper results than conventional down-sampling methods, without blur effects and aliasing.