• Korean Journal of Remote Sensing
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• v.24 no.3
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• pp.257-266
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• 2008

This study presents an approach to synthesize multispectral images at a higher resolution by exploiting a high-resolution image acquired in panchromatic modality. The synthesized images should be similar to the multispectral images that would have been observed by the corresponding sensor at the same high resolution. The proposed scheme is designed to reconstruct the multispectral images at the higher resolution with as less color distortion as possible. It uses a regression model of the second order to fit panchromatic data to multispectral observations. Based on the regression model, the multispectral images at the higher spatial resolution of the panchromatic image are optimized by a quadratic programming. In this study, the new method was applied to the IKONOS 1m panchromatic and 4m multispectral data, and the results were compared with them of several current approaches. Experimental results demonstrate that the proposed scheme can achieve significant improvement over other methods.

• 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.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.3 s.309
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• pp.84-91
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• 2006

In this paper, we present a new segmentation algorithm for color images based on mathematical morphology and a Gaussian mixture model(GMM). We use the morphological operations to determine the number of components in a mixture model and to detect their modes of each mixture component. Next, we have adopted the GMM to represent the probability distribution of color feature vectors and used the deterministic annealing expectation maximization (DAEM) algorithm to estimate the parameters of the GMM that represents the multi-colored objects statistically. Finally, we segment the color image by using posterior probability of each pixel computed from the GMM. The experimental results show that the morphological operation is efficient to determine a number of components and initial modes of each component in the mixture model. And also it shows that the proposed DAEM provides a global optimal solution for the parameter estimation in the mixture model and the natural color images are segmented efficiently by using the GMM with parameters estimated by morphological operations and the DAEM algorithm.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.1
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• pp.57-64
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• 2013

In this paper, we propose the classification method of medicine bottle images using the features with color and size information. It is difficult to classify with size feature only, because there are many similar sizes of bottles. Therefore, we suggest a classification method based on color information, which robust to illumination variations. First, we extract MBR(Minimum Boundary Rectangle) of medicine bottle area using Binary Threshold of Red, Green, and Blue in image and classify images with size. Then, hue information and RGB color average rate are used to classify image, which features are robust to lighting variations. Finally, using SURF(Speed Up Robust Features) algorithm, corresponding image can be found from candidates with previous extracted features. The proposed method makes to reduce execution time and minimize the error rate and is confirmed to be reliable and efficient from experiment.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.1
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• pp.53-61
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• 2010

In this paper, we present a color interpolation algorithm that uses novel edge direction estimator and region classifier. The proposed edge direction estimator accurately determines the edge direction based on the correlation between the images obtained by the channel separated and down-sampled Bayer color filter array(CFA) pattern. The correlation is defined based on the similarity between the edge direction in the local region of the image and the shifting direction of the images. Also, the region of an image is defined as the flat, the edge, and the pattern-edge regions, where the edges are appeared repeatedly. When all the pixels in the image are classified into the three different regions, each pixel is interpolated horizontally or vertically according to the estimated direction. Experimental results show that the proposed algorithm outperforms the conventional edge-directed methods on objective and subjective criteria.

• Journal of Digital Contents Society
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• v.19 no.8
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• pp.1463-1469
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• 2018

The development of multimedia devices with built-in cameras such as smart devices and various studies using video-related multimedia data such as images and video obtained from the devices have been actively conducted. These studies deal with image data. An image can be defined as a set of color information obtained from a digital sensor called a pixel. Images contain various cognitive information such as color, lighting, objects and so on. In order to extract or process such information, it is necessary to clearly understand the composition of colors. In this paper, we introduce 3-dimensional information visualization method which can effectively express the results of image processing together with color distribution. This study visualizes the characteristics of image related multimedia data as well as the characteristics of various analytical data derived from it, so that researchers can transmit the image information more clearly and effectively.

• Journal of the Korea Society of Computer and Information
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• v.16 no.12
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• pp.43-48
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• 2011

Among various methods proposed earlier, fuzzy image filtering is usually one of the favored techniques because it has less blurring effect and the decrease of noise removal rate after filtering. However, fuzzy filtering is ineffective on color images since it is firstly developed with gray scale. Thus, in this paper, we propose a fuzzy filtering algorithm for color images. First, we divide RGB color information from image into three channels of R, G, and B and judge the possibility of each pixel with mask by fuzzy logic independently. The output pixel value might be the average or median according to the degree of noise. Our experiment successfully verifies the effectiveness of new algorithm in color image.

• Smart Media Journal
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• v.3 no.4
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• pp.22-27
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• 2014

Three-dimensional image reconstruction allows us to represent real objects in the virtual space and observe the objects at arbitrary view points. This technique can be used in various application areas such as education, culture, and art. In this paper, we propose an implementation method of the high-quality three-dimensional object using multiple Kinect cameras released from Microsoft. First, We acquire color and depth images from triple Kinect cameras; Kinect cameras are placed in front of the object as a convergence form. Because original depth image includes some areas where have no depth values, we employ joint bilateral filter to refine these areas. In addition to the depth image problem, there is an color mismatch problem in color images of multiview system. In order to solve it, we exploit an color correction method using three-dimensional geometry. Through the experimental results, we found that three-dimensional object which is used the proposed method is more naturally represented than the original three-dimensional object in terms of the color and shape.

• Journal of KIISE:Computing Practices and Letters
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• v.8 no.6
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• pp.692-704
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• 2002

In this paper, we present am image retrieval method based on color-spatial features using quadtree and texture information extracted from object MBRs in an image. Tile proposed method consists of creating a DC image from an original image, changing a color coordinate system, and decomposing regions using quadtree. As such, conditions are present to decompose the DC image, then the system extracts representative colors from each region. And, image segmentation is used to search for object MBRs, including object themselves, object included in the background, or certain background region, then the wavelet coefficients are calculated to provide texture information. Experiments were conducted using the proposed similarity method based on color-spatial and texture features. Our method was able to refute the amount of feature vector storage by about 53%, but was similar to the original image as regards precision and recall. Furthermore, to make up for the deficiency in using only color-spatial features, texture information was added and the results showed images that included objects from the query images.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.49 no.1
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• pp.67-72
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• 2012

In this paper, we present an image enhancement method for atmospherically degraded images using atmospheric light and transmission based on color analysis. We first generate a normalized image using maximum value of each RGB color channel. Then, each atmospheric light is estimated from RGB color channel respectively by calculating reflectance of an image. We also, generate a transmission using gamma coefficients from the Y channel of the image. We can significantly enhance the visibility of an image by using the estimated atmospheric light and the transmission. The proposed algorithm can remove atmospheric degradation components better than existing techniques because the color prevents color distortion which is common problem of existing techniques. Experimental results demonstrate that the proposed algorithm can improve visibility be removing fog, smoke, and dust.