• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.1
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• pp.192-210
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• 2024

Most frequency-domain remote sensing image watermarking algorithms embed watermarks at random locations, which have negative impact on the watermark invisibility. In this study, we propose an adaptive watermarking scheme for remote sensing images that considers the information complexity to select where to embed watermarks to improve watermark invisibility without affecting algorithm robustness. The scheme converts remote sensing images from RGB to YCbCr color space, performs two-level DWT on luminance Y, and selects the high frequency coefficient of the low frequency component (HH^Y₂) as the watermark embedding domain. To achieve adaptive embedding, HH^Y₂ is divided into several 8*8 blocks, the entropy of each sub-block is calculated, and the block with the maximum entropy is chosen as the watermark embedding location. During embedding phase, the watermark image is also decomposed by two-level DWT, and the resulting high frequency coefficient (HH^W₂) is then embedded into the block with maximum entropy using α- blending. The experimental results show that the watermarked remote sensing images have high fidelity, indicating good invisibility. Under varying degrees of geometric, cropping, filtering, and noise attacks, the proposed watermarking can always extract high identifiable watermark images. Moreover, it is extremely stable and impervious to attack intensity interference.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.43 no.11 s.353
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• pp.26-36
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• 2006

In this paper, we propose a cost-effective color filter may (CFA) demosaicing method for digital still cameras in which a single CCD or CMOS image sensor is used. Since a CFA is adopted, we must interpolate missing color values in the red, green and blue channels at each pixel location. While most state-of-the-art algorithms invest a great deal of computational effort in the enhancement of the reconstructed image to overcome the color artifacts, we focus on eliminating the color artifacts with low computational complexity. Using spatial correlation of the adjacent pixels, the edge-directional information of the neighbor pixels is used for determining the edge direction of the current pixel. We apply our method to the state-of-the-art algorithms which use edge-directed methods to interpolate the missing color channels. The experiment results show that the proposed method enhances the demosaiced image qualify from $0.09{\sim}0.47dB$ in PSNR depending on the basis algorithm by removing most of the color artifacts. The proposed method was implemented and verified successfully using verilog HDL and FPGA. It was synthesized to gate-level circuits using 0.25um CMOS standard cell library. The total logic gate count is 12K, and five line memories are used.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.12 no.2
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• pp.45-52
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• 2002

In this contributions, we propose a new MSB(most significant bit) algorithm based on AOP(All One Polynomial) and two parallel semi-systolic architectures to computes $AB^2$over finite field $GF(2^m)$. The proposed architectures are based on standard basis and use the property of irreducible AOP(All One Polynomial) which is all coefficients of 1. The proposed parallel semi-systolic architecture(PSM) has the critical path of $D_{AND2^+}D_{XOR2}$ per cell and the latency of m+1. The modified parallel semi-systolic architecture(WPSM) has the critical path of $D_{XOR2}$ per cell and has the same latency with PSM. The proposed two architectures, PSM and MPSM, have a low latency and a small hardware complexity compared to the previous architectures. They can be used as a basic architecture for exponentiation, division, and inversion. Since the proposed architectures have regularity, modularity and concurrency, they are suitable for VLSI implementation. They can be used as a basic architecture for algorithms, such as the Diffie-Hellman key exchange scheme, the Digital Signature Algorithm(DSA), and the ElGamal encryption scheme which are needed exponentiation operation. The application of the algorithms can be used cryptosystem implementation based on elliptic curve.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.5
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• pp.103-111
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• 2007

In this paper, we propose a VLSI architecture of hardware optimized high quality image signal processor for a Single-chip CMOS Image Sensor(CIS). The Single-chip CIS is usually used for mobile applications, so it has to be implemented as small as possible while maintaining the image quality. Several image processing algorithms are used in ISP to improve captured image quality. Among the several image processing blocks, demosaicing and image filter are the core blocks in ISP. These blocks need line memories, but the number of line memories is limited in a low cost Single-chip CIS. In our design, high quality edge-adaptive and cross channel correlation considered demosaicing algorithm is adopted. To minimize the number of required line memories for image filter, we share the line memories using the characteristics of demosaicing algorithm which consider the cross correlation. Based on the proposed method, we can achieve both high quality and low hardware complexity with a small number of line memories. The proposed method was implemented and verified successfully using verilog HDL and FPGA. It was synthesized to gate-level circuits using 0.25um CMOS standard cell library. The total logic gate count is 37K, and seven and half line memories are used.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.3
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• pp.630-637
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• 2018

Harmony search (HS) is a recently developed metaheuristic optimization algorithm. HS is inspired by the process of musical improvisation and repeatedly searches for the optimal solution using three operations: random selection, memory recall (or harmony memory consideration), and pitch adjustment. HS has been applied by many researchers in various fields. The increasing complexity of real-world optimization problems has created enormous challenges for the current technique, and improved techniques of optimization algorithms and HS are required. We propose an improved clustering harmony search (ICHS) that uses a clustering technique to group solutions in harmony memory based on their objective function values. The proposed ICHS performs modified harmony memory consideration in which decision variables of solutions in a high-ranked cluster have higher probability of being selected than those in a low-ranked cluster. The ICHS is demonstrated in various optimization problems, including mathematical benchmark functions and water distribution system pipe design problems. The results show that the proposed ICHS outperforms other improved versions of HS.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.47 no.2
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• pp.40-46
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• 2010

Multi-user MIMO (Multiple-Input Multiple-Output) systems require collaborative PF schedulers to improve the performance of the log sum of average transmission rates. While the performance of single cell based conventional PF schedulers has been evaluated over various channel conditions, scheduling algorithms by multiple base stations which select multiple users over a given time frame and their performance require further investigations. In this paper, we apply a collaborative PF scheduler to the distributed multi-user MIMO system, which assigns radio resources to multiple users by exchanging user channel information from base stations located in three adjacent sectors. We further evaluate its performance in terms of the log sum of average transmission rates. The performance is compared to that of the full-search collaborative PF scheduler which searches over all possible combinations of user groups, and that of a parallel PF scheduler that determines users without channel information exchange among base stations. We show the log sum of average transmission rates of the collaborative PF scheduler outperforms that of the parallel PF scheduler in low percentile region. In addition, the collaborative PF scheduler exhibits a negligible performance degradation when compared to the full-search collaborative PF scheduler while a significant reduction of the computational complexity is achievable at the same time.

• Journal of Software Engineering Society
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• v.27 no.1
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• pp.8-14
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• 2018

As cloud computing has emerged as a hot trend in the IT industry, various types of cloud services have emerged. In addition, cloud service broker (CSB) technology has emerged to alleviate the complexity of the process of selecting the desired service that user wants among the various cloud services. One of the key features of the CSB is to recommend the best cloud services to users. In general, CSB can use a method to evaluate a service by receiving feedback about a service from users in order to recommend a cloud service. However, since each user has different criteria for giving a rating, there is a problem that reliability of service evaluation can be low when the rating is only used. In this paper, a method is proposed to supplement evaluation of rating based service by applying machine learning based sentiment analysis to cloud service user's review. In addition, the CSB prototype is implemented based on proposed method. Further, the results of comparing the performance of various learning algorithms is proposed that can be used for sentiment analysis through experiments using actual cloud service review as learning data. The proposed service evaluation method complements the disadvantages of the existing rating-based service evaluation and can reflect the service quality in terms of user experience.

• Journal of the HCI Society of Korea
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• v.1 no.1
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• pp.53-61
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• 2006

In this paper, we propose a novel method for 3D reconstruction of an indoor scene using a multi-view camera. Until now, numerous disparity estimation algorithms have been developed with their own pros and cons. Thus, we may be given various sorts of depth images. In this paper, we deal with the generation of a 3D surface using several 3D point clouds acquired from a generic multi-view camera. Firstly, a 3D point cloud is estimated based on spatio-temporal property of several 3D point clouds. Secondly, the evaluated 3D point clouds, acquired from two viewpoints, are projected onto the same image plane to find correspondences, and registration is conducted through minimizing errors. Finally, a surface is created by fine-tuning 3D coordinates of point clouds, acquired from several viewpoints. The proposed method reduces the computational complexity by searching for corresponding points in 2D image plane, and is carried out effectively even if the precision of 3D point cloud is relatively low by exploiting the correlation with the neighborhood. Furthermore, it is possible to reconstruct an indoor environment by depth and color images on several position by using the multi-view camera. The reconstructed model can be adopted for interaction with as well as navigation in a virtual environment, and Mediated Reality (MR) applications.

• The KIPS Transactions:PartB
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• v.12B no.3 s.99
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• pp.223-232
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• 2005

In this paper, we propose a novel post-filtering algorithm with low computational complexity that improves the visual quality of decoded images using block boundary classification and simple adaptive filter (SAF). At first, each block boundary is classified into smooth or complex sub-region. And for smooth-smooth sub-regions, the existence of blocking artifacts is determined using blocky strength. And simple adaptive filtering is processed in each block boundary area. The proposed method processes adaptively, that is, a nonlinear 1-D 8-tap filter is applied to smooth-smooth sub-regions with blocking artifacts, and for smooth-complex or complex-smooth sub-regions, a nonlinear 1-D variant filter is applied to block boundary pixels so as to reduce the blocking and ringing artifacts. And for complex-complex sub-regions, a nonlinear 1-D 2-tap filter is only applied to adjust two block boundary pixels so as to preserve the image details. Experimental results show that the proposed algorithm produced better results than those of conventional algorithms both subjective and objective viewpoints.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.48 no.5
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• pp.88-98
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• 2011

Recently, according as the importance of GIS(geography information system) database security is embossed, much researches had been achieved about GIS network security. But most such researches are weak against sourceful illegal reproductions and distributions of GIS vector data map. In this paper, we proposed an efficient layer unit contents based partial encryption technique in the vector map compression domain to prevent illegal distributions and unauthorized accesses. This method achieves a partial encryption about each central coordinate and directional parameters of a MCA(minimum coding attribute) that is created at the vector map compression processing in the vector space. First, the position encryption is applied as permutating randomly the center coordinate of each record that is minimum unit of vector map shape. And second, the direction encryption that changing shapes of vector map topography is applied as encrypting the direction of vertices's coordinates of each record. In experimental results, we confirmed that our proposed method can encipher the large volumed vector map data effectively in low computational complexity. Also, we could minimize the decline of compression efficiency that occurred by conventional contents based encryption schemes using AES or DES algorithms.