• Korean Journal of Remote Sensing
• /
• v.39 no.5_4
• /
• pp.1097-1109
• /
• 2023

Urban is an area where small-scale changes to individual buildings occur frequently. An existing urban building database requires periodic updating to increase its usability. However, there are limitations in data collection for building changes over a wide urban. In this study, we check the possibility of detecting building changes and updating a building database by using satellite images that can capture a wide urban region by a single image. For this purpose, building areas in a satellite image are first extracted by projecting 3D coordinates of building corners available in a building database onto the image. Building areas are then divided into roof and facade areas. By comparing textures of the roof areas projected, building changes such as height change or building removal can be detected. New height values are estimated by adjusting building heights until projected roofs align to actual roofs observed in the image. If the projected image appeared in the image while no building is observed, it corresponds to a demolished building. By checking buildings in the original image whose roofs and facades areas are not projected, new buildings are identified. Based on these results, the building database is updated by the three categories of height update, building deletion, or new building creation. This method was tested with a KOMPSAT-3A image over Incheon Metropolitan City and Incheon building database available in public. Building change detection and building database update was carried out. Updated building corners were then projected to another KOMPSAT-3 image. It was confirmed that building areas projected by updated building information agreed with actual buildings in the image very well. Through this study, the possibility of semi-automatic building change detection and building database update based on single satellite image was confirmed. In the future, follow-up research is needed on technology to enhance computational automation of the proposed method.

• The Transactions of the Korea Information Processing Society
• /
• v.2 no.4
• /
• pp.524-534
• /
• 1995

Image segmentation is a process of partitioning of an image into different regions that have similar properties. It is an old and difficult problem. They have developed many image segmentation systems and have studied to evaluate the existing segmentation systems. However, evaluation of image segmentation systems is very difficult in nature. In this paper, we propose the evaluation criteria that evaluate image segmentation systems automatically. In order to overcome the drawbacks of using only a single evaluation criterion, we have incorporated four evaluation criteria, that is, boundary difference, boundary consistency, region uniformity, and region difference. As the experimental results show, our evaluation criteria performs very well.

• Journal of the Korea Society of Computer and Information
• /
• v.25 no.3
• /
• pp.51-55
• /
• 2020

In this paper, an improved FAM is proposed by adopting similarity learning in the existing FAM (Fuzzy Associative Memory) used in image restoration. Image restoration refers to the recovery of the latent clean image from its noise-corrupted version. In serious application like face recognition, this process should be noise-tolerant, robust, fast, and scalable. The existing FAM is a simple single layered neural network that can be applied to this domain with its robust fuzzy control but has low capacity problem in real world applications. That similarity measure is implied to the connection strength of the FAM structure to minimize the root mean square error between the recovered and the original image. The efficacy of the proposed algorithm is verified with significant low error magnitude from random noise in our experiment.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.9 no.10
• /
• pp.1189-1195
• /
• 2014

In this study we propose an image denoising algorithm which manipulates the information obtained from multiple images in the same environment for mobile smart phones. We also envisage a multiple images registration method for mobile smart phone cameras equipped with limited computing ability and present an effective image denoising algorithm combining and manipulating the information obtained from multiple images. We proved that the proposed algorithm has much better PSNR value than the method applying single image. We verified that the propose approach has good denoising quality and can be utilized in the feasible level speed on Android smart phones.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.33 no.6
• /
• pp.517-526
• /
• 2015

Among the various image fusion or pan-sharpening methods, those wavelet-based methods provide superior radiometric quality. However, the fusion processing is not only simple but also flexible, since many low- and high-frequency sub-bands are often produced in the wavelet domain. To address this issue, a novel DT-CWT (Dual-Tree Complex Wavelet Transform) proportional to the fusion method by a WZP (Wavelet Zero-Padding) is proposed. The proposed method produces a single high-frequency image in the spatial domain that is injected into the LRM (Low-Resolution Multispectral) image. Thus, a wavelet domain fusion can be simplified to spatial domain fusion. In addition, in the proposed DT-CWTP (DT-CWT Proportional) fusion method, it is unnecessary to decompose the LRM image by adopting WZP. The comparison indicates that the proposed fusion method is nearly five times faster than the DT-CWT with SW (Substitute-Wavelet) fusion method, meanwhile simultaneously maintaining the radiometric quality. The conducted experiments with WorldView-2 satellite images demonstrated promising results with the computation efficiency and fused image quality.

• Journal of Computational Design and Engineering
• /
• v.2 no.1
• /
• pp.26-37
• /
• 2015

A lot of researchers have been investigating interactive portable projection systems such as a mini-projector. In addition, in exhibition halls and museums, there is a trend toward using interactive projection systems to make viewing more exciting and impressive. They can also be applied in the field of art, for example, in creating shadow plays. The key idea of the interactive portable projection systems is to recognize the user's gesture in real-time. In this paper, a vision-based shadow gesture recognition method is proposed for interactive projection systems. The gesture recognition method is based on the screen image obtained by a single web camera. The method separates only the shadow area by combining the binary image with an input image using a learning algorithm that isolates the background from the input image. The region of interest is recognized with labeling the shadow of separated regions, and then hand shadows are isolated using the defect, convex hull, and moment of each region. To distinguish hand gestures, Hu's invariant moment method is used. An optical flow algorithm is used for tracking the fingertip. Using this method, a few interactive applications are developed, which are presented in this paper.

• Journal of Internet Computing and Services
• /
• v.11 no.2
• /
• pp.173-184
• /
• 2010

The advancement of ubiquitous networks facilitates and increases access to the Internet via mobile devices, which offers the advantages of enhanced mobility and accessibility. While Mobile Internet is largely free of temporal and spatial restrictions, producing content for mobile websites is a challenging work due to the existence of multiple device types and markup languages. This paper proposes a technique that makes use of image maps to improve the visual consistency of mobile web content displayed on a variety of mobile devices. The proposed image map method captures several objects comprising the webpage into a single image, and provides the image in Mobile Web services. Mobile devices employing the proposed method can reorganize webpages with multiple objects more easily and obtain the visually identical content on their screen.

• Transactions of the Korean Society of Mechanical Engineers B
• /
• v.24 no.6
• /
• pp.760-768
• /
• 2000

Filter efficiency of electrically charged particle in uncharged fibrous filter was measured. In previous studies, the effect of charged particle on filter efficiency was investigated but there was difficulty in measuring of image effect that is appeared at the charged small particle. We could easily measure the image effect with charging small particles by photoelectric charging. The spark discharge aerosol generator and a differential mobility analyzer (DMA) were used to generate sub-micron monodisperse particles (${\leq}200$ nm). The generated particles were charged in photoelectric charging process using ultraviolet lamp and electric field. The filter efficiency of the charged particles, classified by another DMA, was measured in filter tester using a condensation nucleus counter (CNC) as function of particle diameter, particle charge and airflow velocity. It is shown that the filter efficiency increases with increasing charge number of the particle and is affected by particle size and flow velocity. Single fiber filter efficiency mainly depends on image force parameter and peclet number. The peclet number was not considered at previous other papers. We propose a modi fied experimental correlation as function of image force parameter and peclet number.

• Journal of Korea Multimedia Society
• /
• v.23 no.2
• /
• pp.135-145
• /
• 2020

Recently, deep-learning based methods for low-light image enhancement accomplish great success through supervised learning. However, they still suffer from the lack of sufficient training data due to difficulty of obtaining a large amount of low-/normal-light image pairs in real environments. In this paper, we propose an unsupervised learning approach for single low-light image enhancement using the bright channel prior (BCP), which gives the constraint that the brightest pixel in a small patch is likely to be close to 1. With this prior, pseudo ground-truth is first generated to establish an unsupervised loss function. The proposed enhancement network is then trained using the proposed unsupervised loss function. To the best of our knowledge, this is the first attempt that performs a low-light image enhancement through unsupervised learning. In addition, we introduce a self-attention map for preserving image details and naturalness in the enhanced result. We validate the proposed method on various public datasets, demonstrating that our method achieves competitive performance over state-of-the-arts.

• Proceedings of the KSRS Conference
• /
• 2007.10a
• /
• pp.625-628
• /
• 2007

We present an efficient and robust technique to estimate the velocity of moving targets from a single SAR image. In SAR images, azimuth image shift is a well known phenomenon, which is observed in moving targets having slant-range velocity. Most methods estimated the velocity of moving targets from the distance difference between the road and moving targets or between ship and the ship wake. However, the methods could not be always applied to moving targets because it is difficult to find the road and the ship wake. We adopted a method estimating the velocity of moving targets from azimuth differentials of range-compressed image. This method is based on an assumption that Doppler center frequency shift of moving target causes a phase difference in azimuth differential values. The phase difference is linearly distorted by Doppler rate due to the geometry of SAR image. The linear distortion is eliminated from phase removal procedure, and the constant phase difference is estimated. Finally, range velocity estimates for moving targets are retrieved. This technique is tested using an ENVISAT ASAR image in which several unknown ships are presented. The theoretical accuracy of this technique is discussed by SAR simulation. The advantages and disadvantages of this method over the conventional method are also discussed.