• Proceedings of the Korean Society of Broadcast Engineers Conference
• /
• 1997.11a
• /
• pp.145-149
• /
• 1997

In this paper, a hierarchical spatio-temporal image segmentation method based on binary split algorithm is proposed. Intensity and displacement vector at each pixel are used for image segmentation. The displacement vectors between two image frames which skip over one or several frames can be approximated by accumulating of the velocity vectors calculated from optical flow between two successive frames when the time interval between the two image frames is short enough or the motion is slow. The pixels whose displacement vector and intensity are ambiguous are precisely decided by the modified watershed algorithm using the proposed priority measure. In the experiment, the region of moving object is precisely segmented.

• Proceedings of the Korean Information Science Society Conference
• /
• 2003.10b
• /
• pp.655-657
• /
• 2003

This study is on the characteristics of discriminating of image using unique electric wave intensity value from satellite images data. Namely this study is on studying specific image characteristics by image spectrum and is on developing procedures discriminating of water, forest. narrow-leaved(coniferous) trees, broad-leaved(deciduous) trees, terrain, farmland, grassland, etc. using unique spectrum value in material. Finally applying this procedures, we design and implement discriminating system, IDEA(Information Discriminating Extracting Agent).

• Journal of applied mathematics & informatics
• /
• v.41 no.5
• /
• pp.1115-1128
• /
• 2023

In this paper, a novel hybrid method for multi-focus image fusion is proposed. The method combines the advantages of wavelet transform-based methods and focus-measure-based methods to achieve an improved fusion result. The input images are first decomposed into different frequency sub-bands using the discrete wavelet transform (DWT). The focus measure of each sub-band is then calculated using the Laplacian of Gaussian (LoG) operator, and the sub-band with the highest focus measure is selected as the focused sub-band. The focused sub-band is sharpened using an unsharp masking filter to preserve the details in the focused part of the image.Finally, the sharpened focused sub-bands from all input images are fused using the maximum intensity fusion method to preserve the important information from all focus images. The proposed method has been evaluated using standard multi focus image fusion datasets and has shown promising results compared to existing methods.

• Journal of Korea Multimedia Society
• /
• v.16 no.2
• /
• pp.169-179
• /
• 2013

Change detection algorithms take two image frames and return the locations of newly introduced objects which cause differences between the images. This paper presents a new change detection method, which classifies intensity changes due to introduced objects, reflected light and shadow from the objects to their neighborhood, and the noise, and exactly localizes the introduced objects. For classification and localization, first we analyze the histogram of the intensity difference between two images, and estimate multiple threshold values. Second we estimate candidate object boundaries using the gradient difference between two images. Using those threshold values and candidate object boundaries, we segment the frame difference image into multiple regions. Finally we classify whether each region belongs to the introduced objects or not using textures in the region. Experiments show that the proposed method exactly localizes the objects in various scenes with different lighting.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.25 no.5
• /
• pp.483-488
• /
• 2015

This paper presents a local binary pattern(LBP) for effectively classifying textures, which is based on the multidimensional intensity difference between the adjacent pixels in the block image. The intensity difference by considering the a extent of 4 directional changes(verticality, horizontality, diagonality, inverse diagonality) in brightness between the adjacent pixels is applied to reduce the computation load as a results of decreasing the levels of histogram for classifying textures of image. And the binary patterns that is represented by the relevant intensities within a block image, is also used to effectively classify the textures by accurately reflecting the local attributes. The proposed method has been applied to classify 24 block images from USC Texture Mosaic #2 of 128*128 pixels gray image. The block images are different in size and texture. The experimental results show that the proposed method has a speedy classification and makes a free size block images classify possible. In particular, the proposed method gives better results than the conventional LBP by increasing the range of histogram level reduction as the block size becomes larger.

• Journal of radiological science and technology
• /
• v.42 no.1
• /
• pp.39-46
• /
• 2019

This study conducted a comparative analysis of differences between cartesian trajectory in a linear rectangular coordinate system and MultiVane trajectory in a nonlinear rectangular coordinate system axial T1 and axial T2 images using an American College of Radiology(ACR) phantom. The phantom was placed at the center of the head coil and the top-to-bottom and left-to-right levels were adjusted by using a level. The experiment was performed according to the Phantom Test Guidance provided by the ACR, and sagittal localizer images were obtained. As shown in Figure 2, slices # 1 and # 11 were scanned after placing them at the center of a $45^{\circ}$ wedge shape, and a total of 11 slices were obtained. According to the evaluation results, the image intensity uniformity(IIU) was 93.34% for the cartesian trajectory, and 93.19% for the MultiVane trajectory, both of which fall under the normal range in the axial T1 image. The IIU for the cartesian trajectory was 0.15% higher than that for the MultiVane trajectory. In axial T2, the IIU was 96.44% for the cartesian trajectory, and 95.97% for the MultiVane trajectory, which fall under the normal range. The IIU for the cartesian trajectory was by 0.47% higher than that for the MultiVane trajectory. As a result, the cartesian technique was superior to the MultiVane technique in terms of the high-contrast spatial resolution, image intensity uniformity, and low-contrast object detectability.

• Journal of the Korean Institute of Landscape Architecture
• /
• v.35 no.4
• /
• pp.90-104
• /
• 2007

Landmarks like high-rise building are one of the important elements for the enhancement of city identity and provides the hierarchy of city streets, playing a central and symbolic role in cities. Research on physical attribute of landmarks, such as height, distance, location and shape, which are suitable for a city scale, can help a city create a distinct image and maintain comprehensible structure. To achieve this purpose, it is necessary to understand the spatial and cognitive characteristics of a landmark for the establishment and management of it. The results of this study can be summarized as follows: 1. The level of representativeness of a landmark increases in proportion to the degree of cognitive intensity on it. The relation between representativeness and cognitive intensity can be explained as the log-function as follows: Log(the number of people who respond "It has representativeness")=$-1.2579+1.5908{\times}$(cognitive intensity); 2. There are a few differences based on the attributes of respondents: while gender has no distinct influence, residential period and age show statistically meaningful influence on cognitive intensity of a vertical landmark Cognitive intensity of an individual landmarks especially, differs according to the class of main users. Because of frequent changes in occupation or employment, respondents consider the distance from a residential area more important than the distance from a working area in evaluating cognitive intensity of landmarks; 3. landmark can be classified into two kinds: a district landmark and an urban landmark A district landmark is closely connected with physical attributes of the landmark itself, such as distance, size and height. An urban landmark is mainly related to cognitive attributes such as the image and identity of a city as a whole. As a result, the landmark analysis data in this research provides spatial order and identity in a city. It is difficult to establish and reinforce the image of a city as a single element ike a landmark. However, withy steady follow-up research, this study could be seen as a systematic and logical model to improve urban landscape and image.

• Journal of Korea Multimedia Society
• /
• v.17 no.2
• /
• pp.143-151
• /
• 2014

In images degraded by bad weather, edges representing object boundaries become weak and faint. In this paper we present an image enhancement method, which increases image visibility by making edges as clear as possible. First, we choose edge candidate regions by finding local maxima and minima in an image intensity field, and then build a histogram using image intensities of pixels located at the two sides of candidate edges. Second, we decompose this histogram into multiple modes, which are determined by local minima in the histogram. Once modes are computed, we find modes connected by edges in the image intensity field and build link chains of connected modes. Finally we choose the longest link chain of modes and make the distances between every connected modes as large as possible. The darkest mode and the brightest mode should be within the image intensity range. This stretch makes edges clear and increases image visibility. Experiments show that the proposed method real-time enhances images degraded by bad weather as good as well known time-consuming methods.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.11 no.3
• /
• pp.1633-1649
• /
• 2017

In remote sensing image processing, the traditional fusion algorithm is based on the Intensity-Hue-Saturation (IHS) transformation. This method does not take into account the texture or spectrum information, spatial resolution and statistical information of the photos adequately, which leads to spectrum distortion of the image. Although traditional solutions in such application combine manifold methods, the fusion procedure is rather complicated and not suitable for practical operation. In this paper, an improved IHS transformation fusion algorithm based on the local variance weighting scheme is proposed for remote sensing images. In our proposal, firstly, the local variance of the SPOT (which comes from French "Systeme Probatoire d'Observation dela Tarre" and means "earth observing system") image is calculated by using different sliding windows. The optimal window size is then selected with the images being normalized with the optimal window local variance. Secondly, the power exponent is chosen as the mapping function, and the local variance is used to obtain the weight of the I component and match SPOT images. Then we obtain the I' component with the weight, the I component and the matched SPOT images. Finally, the final fusion image is obtained by the inverse Intensity-Hue-Saturation transformation of the I', H and S components. The proposed algorithm has been tested and compared with some other image fusion methods well known in the literature. Simulation result indicates that the proposed algorithm could obtain a superior fused image based on quantitative fusion evaluation indices.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.28 no.8C
• /
• pp.827-834
• /
• 2003

In this paper, we implemented an optical information security system using computer generated hologram based on the principle of interference and BaTiO$_3$that is photorefractive material. First of all, we would generate binary phase hologram which can reconstruct the original image perfectly, and regard this hologram as the image to be encrypted. And then applying the interference rule to the hologram, encrypted and reference (fkey information) images are generated. In the decrypting process, we can get an interference intensity by interfering the reference image and the encrypted image in the Mach-Zehnder interferometer. and transforming interference intensity information into phase information using LCD(liquid crystal display) and finally recover original image by inverse Fourier transforming the phase information. In this process, the Intensity information generated by interference of two images is very sensitive to external vibrations. So, we get a stable interference using the characteristic of SPPCM(self pumped phase conjugate mirror) of BaTiO$_3$that is photorefractive material. The proposed method has an advantage of double image encryption by encrypting the hologram of the image instead of original image.