• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.7
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• pp.4475-4481
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• 2014

A histogram equalization method have been used traditionally for the image enhancement of low quality images. This uses the transformation function, which is a cumulative density function of an input image, and it has mathematically maximum entropy. This method, however, may yield whitening artifacts. This paper proposes the weighted histogram equalization method based on histogram equalization. It has Weber-Fechner's law for a human's vision characteristics, and a dynamic range modification to solve the problem of some methods, which yield a transformation function, regardless of the input image. Finally, the proposed transformation function was calculated using the weighted average of Weber-Fechner and the histogram equalization transformation functions in a modified dynamic range. The simulation results showed that the proposed algorithm effectively enhances the contrast in terms of the subjective quality. In addition, the proposed method has similar or higher entropy than the other conventional approaches.

• Journal of Korean Society for Geospatial Information Science
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• v.19 no.4
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• pp.55-63
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• 2011

Having a wide angle of view, a fisheye lens is useful for obtaining images of the inside wall of a tunnel. A circular fisheye tunnel image can be transformed into a familiar rectangular image by applying the concept of cylindrical projection. This projection transformation causes several types of distortions in the projected image. This paper discusses the distortion on the boundary lines between smoothly curved wall and flat ground. We analyzed the cause of this boundary distortion, developed transformation model, and derived a correction formular. A distortion correction software programmed in Visual C++ applied to projected image. Consequently, boundary-corrected image could be obtained. Research into other distortions of projected image will helpful in obtaining tunnel image that resembles real tunnel from fisheye tunnel image.

• IEIE Transactions on Smart Processing and Computing
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• v.4 no.5
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• pp.311-317
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• 2015

The aim of this study is to develop a 3D registration algorithm for positron emission tomography/computed tomography (PET/CT) and magnetic resonance (MR) images acquired from independent PET/CT and MR imaging systems. Combined PET/CT images provide anatomic and functional information, and MR images have high resolution for soft tissue. With the registration technique, the strengths of each modality image can be combined to achieve higher performance in diagnosis and radiotherapy planning. The proposed method consists of two stages: normalized mutual information (NMI)-based global matching and independent component analysis (ICA)-based refinement. In global matching, the field of view of the CT and MR images are adjusted to the same size in the preprocessing step. Then, the target image is geometrically transformed, and the similarities between the two images are measured with NMI. The optimization step updates the transformation parameters to efficiently find the best matched parameter set. In the refinement stage, ICA planes from the windowed image slices are extracted and the similarity between the images is measured to determine the transformation parameters of the control points. B-spline. based freeform deformation is performed for the geometric transformation. The results show good agreement between PET/CT and MR images.

• Journal of Korea Multimedia Society
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• v.7 no.8
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• pp.1046-1057
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• 2004

An image enhancement method using both homomorphic transformation and multiscale decomposition is proposed. The original image is first transformed to homomorphic domain by taking the logarithm, is then separated to multiscales. These multiscales are combined with weighting. The combined signal is exponentially transformed back into intensity domain. In homomorphic domain, the magnitude control of low frequency component make change the dynamic range, and the magnitude control of the other frequency components contribute to enhancement of the contrast. The "${\AA}$ trous" algorithm, which has a simple and efficient scheme, is used for multiscale decomposition. The performance of proposed method is verified by simulation.

• Journal of Electrical Engineering and Technology
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• v.8 no.5
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• pp.1188-1193
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• 2013

In content based image retrieval (CBIR) system, the images are represented based upon its feature such as color, texture, shape, and spatial relationship etc. In this paper, we propose a MRI Image Retrieval using wavelet transform with mahalanobis distance measurement. Wavelet transformation can also be easily extended to 2-D (image) or 3-D (volume) data by successively applying 1-D transformation on different dimensions. The proposed algorithm has tested using wavelet transform and performance analysis have done with HH and $H^*$ elimination methods. The retrieval image is the relevance between a query image and any database image, the relevance similarity is ranked according to the closest similar measures computed by the mahalanobis distance measurement. An adaptive similarity synthesis approach based on a linear combination of individual feature level similarities are analyzed and presented in this paper. The feature weights are calculated by considering both the precision and recall rate of the top retrieved relevant images as predicted by our enhanced technique. Hence, to produce effective results the weights are dynamically updated for robust searching process. The experimental results show that the proposed algorithm is easily identifies target object and reduces the influence of background in the image and thus improves the performance of MRI image retrieval.

• Journal of the Korea Society of Computer and Information
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• v.3 no.3
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• pp.7-15
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• 1998

In this paper a calibration method is proposed for calibrating distorted image from lens and various factors. The similar origin image can be generated by the proposed method that calculate a calibration coefficient by modeling third transformation between standard image and distorted image and then apply the coefficient to distorted image The coefficient is effective until camera position is changed or lens is exchanged. This research consists of processes to calculate calibration coefficient and to set similar real image by the coefficient. Proposed method especially is applied to a system to obtain a real image from a distorted image causing effects of special system environment and camera lens The advantage of this method is verified by experiment using distorted images from a CCD camera that will attach atomic pile.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.698-701
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• 2005

This paper examines that is extracted certain information in forest areas within high resolution imagery based on wavelet transformation. First of all, study areas are selected one more species distributed spots refer to forest type map. Next, study area is cut 256 x 256 pixels size because of image processing problem in large volume data. Prior to wavelet transformation, five texture parameters (contrast, dissimilarity, entropy, homogeneity, Angular Second Moment (ASM≫ calculated by using Gray Level Co-occurrence Matrix (GLCM). Five texture images are set that shifting window size is 3x3, distance .is 1 pixel, and angle is 45 degrees used. Wavelet function is selected Daubechies 4 wavelet basis functions. Result is summarized 3 points; First, Wavelet transformation images derived from contrast, dissimilarity (texture parameters) have on effect on edge elements detection and will have probability used forest road detection. Second, Wavelet fusion images derived from texture parameters and original image can apply to forest area classification because of clustering in Homogeneous forest type structure. Third, for grading evaluation in forest fire damaged area, if data fusion of established classification method, GLCM texture extraction concept and wavelet transformation technique effectively applied forest areas (also other areas), will obtain high accuracy result.

• Journal of the Korean Graphic Arts Communication Society
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• v.25 no.1
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• pp.121-133
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• 2007

The CMS(color management system) software was to enable consistent color reproduction from original to reproduction. The CMS was to create RGB monitor and printer characterization profiles and then use the profiles for device independent color transformation. The implemented CMM(color management module) used the CIELAB color space for the profile connection. Various monitor characterization model was evaluated for proper color transformation. To construct output device profile, SLI(sequential linear interpolation) method was used for the color conversion from CMYK device color to device independent CIELAB color space and tetrahedral interpolation method was used for backward transformation. UCR(under color removal) based black generation algorithm was used to construct CIELAB to CMYK LUT(lookup table). When transforming the CIE Lab colour space to CMYK, it was possible to involve the gray revision method regularized in the brightness into colour transformation process and optimize the colour transformation by black generation method based on UCR technique. For soft copy colour proofing, evaluating several monitor specialism methods showed that LUT algorithm was useful. And it was possible to simplify colour gamut mapping by constructing both the look-up table and the colour gamut mapping algorithm to a reference table.

• Communications for Statistical Applications and Methods
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• v.16 no.3
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• pp.409-419
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• 2009

In this article, an explicit solution of the EM algorithm for the image deburring is presented. To obtain the restore image from the strictly iterative EM algorithm is quite time-consumed and impractical in particular when the underlying observed image is not small and the number of iterations required to converge is large. The explicit solution provides a quite reasonable restore image although it exploits the approximation in the outside of the valid area of image, and also allows to obtain the effective EM solutions without iteration process in real-time in practice by using the discrete finite Fourier transformation.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.5
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• pp.331-341
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• 2019

With the popularity of sensor-rich environments, smartphones have become one of the major platforms for obtaining and sharing information. Since it is difficult to utilize GNSS (Global Navigation Satellite System) inside the area with many buildings, the localization of smartphone in this case is considered as a challenging task. To resolve problem of localization using smartphone a four step image-based localization method and procedure is proposed. To improve the localization accuracy of smartphone datasets, MMS (Mobile Mapping System) and Google Street View were utilized. In our approach first, the searching for candidate matching image is performed by the query image of smartphone's using GNSS observation. Second, the SURF (Speed-Up Robust Features) image matching between the smartphone image and reference dataset is done and the wrong matching points are eliminated. Third, the geometric transformation is performed using the matching points with 2D affine transformation. Finally, the smartphone location and attitude estimation are done by PnP (Perspective-n-Point) algorithm. The location of smartphone GNSS observation is improved from the original 10.204m to a mean error of 3.575m. The attitude estimation is lower than 25 degrees from the 92.4% of the adjsuted images with an average of 5.1973 degrees.