• Title/Summary/Keyword: parametric image

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An Image Interpolation by Adaptive Parametric Cubic Convolution (3차 회선 보간법에 적응적 매개변수를 적용한 영상 보간)

  • Yoo, Jea-Wook;Park, Dae-Hyun;Kim, Yoon
    • Journal of the Korea Society of Computer and Information
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    • v.13 no.6
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    • pp.163-171
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    • 2008
  • In this paper, we present an adaptive parametric cubic convolution technique in order to enlarge the low resolution image to the high resolution image. The proposed method consists of two steps. During the first interpolation step, we acquire adaptive parameters in introducing a new cost-function to reflect frequency properties. And, the second interpolation step performs cubic convolution by applying the parameters obtained from the first step. The enhanced interpolation kernel using adaptive parameters produces output image better than the conventional one using a fixed parameter. Experimental results show that the proposed method can not only provides the performances of $0.5{\sim}4dB$ improvements in terms of PSNR, but also exhibit better edge preservation ability and original image similarity than conventional methods in the enlarged images.

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Image Feature Detection and Contrast Enhancement Algorithms Based on Statistical Tests

  • Kim, Yeong-Hwa;Nam, Ji-Ho
    • Journal of the Korean Data and Information Science Society
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    • v.18 no.2
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    • pp.385-399
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    • 2007
  • In many image processing applications, a random noise makes some trouble since most video enhancement functions produce visual artifacts if a priori of the noise is incorrect. The basic difficulty is that the noise and the signal are difficult to be distinguished. Typical unsharp masking (UM) enhances the visual appearances of images, but it also amplifies the noise components of the image. Hence, the applications of a UM are limited when noises are presented. This paper proposed statistical algorithms based on parametric and nonparametric tests to adaptively enhance the image feature and the noise combining while applying UM. With the proposed algorithm, it is made possible to enhance the local contrast of an image without amplifying the noise.

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Study on the Improvement of Indirect Intra-Oral Dental Digital X-ray Image Sensor with Optical Coupling

  • Whang, Joo-Ho;Chung, Jin-Bum;Kim, Tae-Woo
    • Nuclear Engineering and Technology
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    • v.33 no.5
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    • pp.514-525
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    • 2001
  • Optimum characteristics of digital X-ray sensor components were analyzed to develop intra- oral dental digital X-ray image sensor using indirect method. Parametric analysis was carried out to optimize the phosphor thickness and the fiber optic plate (FOP) coupling to charge coupled device (CCD). X-ray absorption and light diffusion in the phosphor layer were analyzed by the Monte Carlo method. Real time X-ray image was obtained with prototype X- ray image sensor using general CCD camera with 1∼10 Ip/mm resolution. It has been previously shown that large resolution degradation in X-ray images was caused by miss alignment of FOP to CCD and optical adhesive selection. In this study, we reported that X-ray image quality was greatly improved by using optimized characteristics of alignment device and phosphor thickness.

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Comparison of Algorithms for Generating Parametric Image of Cerebral Blood Flow Using ${H_2}^{15}O$ PET Positron Emission Tomography (${H_2}^{15}O$ PET을 이용한 뇌혈류 파라메트릭 영상 구성을 위한 알고리즘 비교)

  • Lee, Jae-Sung;Lee, Dong-Soo;Park, Kwang-Suk;Chung, June-Key;Lee, Myung-Chul
    • The Korean Journal of Nuclear Medicine
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    • v.37 no.5
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    • pp.288-300
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    • 2003
  • Purpose: To obtain regional blood flow and tissue-blood partition coefficient with time-activity curves from ${H_2}^{15}O$ PET, fitting of some parameters in the Kety model is conventionally accomplished by nonlinear least squares (NLS) analysis. However, NLS requires considerable compuation time then is impractical for pixel-by-pixel analysis to generate parametric images of these parameters. In this study, we investigated several fast parameter estimation methods for the parametric image generation and compared their statistical reliability and computational efficiency. Materials and Methods: These methods included linear least squres (LLS), linear weighted least squares (LWLS), linear generalized least squares (GLS), linear generalized weighted least squares (GWLS), weighted Integration (WI), and model-based clustering method (CAKS). ${H_2}^{15}O$ dynamic brain PET with Poisson noise component was simulated using numerical Zubal brain phantom. Error and bias in the estimation of rCBF and partition coefficient, and computation time in various noise environments was estimated and compared. In audition, parametric images from ${H_2}^{15}O$ dynamic brain PET data peformed on 16 healthy volunteers under various physiological conditions was compared to examine the utility of these methods for real human data. Results: These fast algorithms produced parametric images with similar image qualify and statistical reliability. When CAKS and LLS methods were used combinedly, computation time was significantly reduced and less than 30 seconds for $128{\times}128{\times}46$ images on Pentium III processor. Conclusion: Parametric images of rCBF and partition coefficient with good statistical properties can be generated with short computation time which is acceptable in clinical situation.

Multiple Linear Analysis for Generating Parametric Images of Irreversible Radiotracer (비가역 방사성추적자 파라메터 영상을 위한 다중선형분석법)

  • Kim, Su-Jin;Lee, Jae-Sung;Lee, Won-Woo;Kim, Yu-Kyeong;Jang, Sung-June;Son, Kyu-Ri;Kim, Hyo-Cheol;Chung, Jin-Wook;Lee, Dong-Soo
    • Nuclear Medicine and Molecular Imaging
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    • v.41 no.4
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    • pp.317-325
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    • 2007
  • Purpose: Biological parameters can be quantified using dynamic PET data with compartment modeling and Nonlinear Least Square (NLS) estimation. However, the generation of parametric images using the NLS is not appropriate because of the initial value problem and excessive computation time. In irreversible model, Patlak graphical analysis (PGA) has been commonly used as an alternative to the NLS method. In PGA, however, the start time ($t^*$, time where linear phase starts) has to be determined. In this study, we suggest a new Multiple Linear Analysis for irreversible radiotracer (MLAIR) to estimate fluoride bone influx rate (Ki). Methods: $[^{18}F]Fluoride$ dynamic PET scans was acquired for 60 min in three normal mini-pigs. The plasma input curve was derived using blood sampling from the femoral artery. Tissue time-activity curves were measured by drawing region of interests (ROls) on the femur head, vertebra, and muscle. Parametric images of Ki were generated using MLAIR and PGA methods. Result: In ROI analysis, estimated Ki values using MLAIR and PGA method was slightly higher than those of NLS, but the results of MLAIR and PGA were equivalent. Patlak slopes (Ki) were changed with different $t^*$ in low uptake region. Compared with PGA, the quality of parametric image was considerably improved using new method. Conclusion: The results showed that the MLAIR was efficient and robust method for the generation of Ki parametric image from $[^{18}F]Fluoride$ PET. It will be also a good alternative to PGA for the radiotracers with irreversible three compartment model.

Modulation Transfer Function (MTF) Measurement for KOMPSAT EOC image data Using Edge Method

  • Song J. H.;Lee D. H.
    • Proceedings of the KSRS Conference
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    • 2004.10a
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    • pp.489-493
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    • 2004
  • The Modulation Transfer Function (MTF) is commonly used to characterize the spatial quality of imaging systems. This work is the attempt to measure the MTF for KOMPSAT EOC using the non-parametric method as ground inputs. The spatial performance of the KOMPSAT EOC was analyzed by edge method while in flight using multi-temporal image data collected over test site in Seoul. The results from this work demonstrate the potential applicability of this method to estimate MTF for high spatial resolution satellite KOMPSAT-2 that is being developed to be launched in 2005.

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Adaptive Parametric Estimation and Classification of Remotely Sensed Imagery Using a Pyramid Structure

  • Kim, Kyung-Sook
    • Korean Journal of Remote Sensing
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    • v.7 no.1
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    • pp.69-86
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    • 1991
  • An unsupervised region based image segmentation algorithm implemented with a pyramid structure has been developed. Rather than depending on thraditional local splitting and merging of regions with a similarity test of region statistics, the algorithm identifies the homogenous and boundary regions at each level of pyramid, then the global parameters of esch class are estimated and updated with values of the homogenous regions represented at the level of the pyramid using the mixture distribution estimation. The image is then classified through the pyramid structure. Classification results obtained for both simulated and SPOT imagery are presented.

Single Image-Based 3D Tree and Growth Models Reconstruction

  • Kim, Jaehwan;Jeong, Il-Kwon
    • ETRI Journal
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    • v.36 no.3
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    • pp.450-459
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    • 2014
  • In this paper, we present a new, easy-to-generate system that is capable of creating virtual 3D tree models and simulating a variety of growth processes of a tree from a single, real tree image. We not only construct various tree models with the same trunk through our proposed digital image matting method and skeleton-based abstraction of branches, but we also animate the visual growth of the constructed 3D tree model through usage of the branch age information combined with a scaling factor. To control the simulation of a tree growth process, we consider tree-growing attributes, such as branching orders, branch width, tree size, and branch self-bending effect, at the same time. Other invisible branches and leaves are automatically attached to the tree by employing parametric branch libraries under the conventional procedural assumption of structure having a local self-similarity. Simulations with a real image confirm that our system makes it possible to achieve realistic tree models and growth processes with ease.

Detection of Edges in Color Images

  • Ganchimeg, Ganbold;Turbat, Renchin
    • IEIE Transactions on Smart Processing and Computing
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    • v.3 no.6
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    • pp.345-352
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    • 2014
  • Edge detection considers the important technical details of digital image processing. Many edge detection operators already perform edge detection in digital color imaging. In this study, the edge of many real color images that represent the type of digital image was detected using a new operator in the least square approximation method, which is a type of numerical method. The Linear Fitting algorithm is computationally more expensive compared to the Canny, LoG, Sobel, Prewitt, HIS, Fuzzy, Parametric, Synthetic and Vector methods, and Robert' operators. The results showed that the new method can detect an edge in a digital color image with high efficiency compared to standard methods used for edge detection. In addition, the suggested operator is very useful for detecting the edge in a digital color image.

Space-Variant B-Spline Functions for Image Interpolation (영상보간을 위한 공간변화(Space-Variant) B-Splin 함수)

  • 이병길;김순자;하영호
    • The Transactions of the Korean Institute of Electrical Engineers
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    • v.40 no.4
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    • pp.394-401
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    • 1991
  • B-spline function is generally used for an image interpolation because of its smoothness and continuity, but it accompanies a large amount of blurring effect. In this paper, a space-variant B-spline interpolation function is proposed through deblurring process followed by de-aliasing process. The proposed function has parametric expression and performs smoothing and edge-enhancement adaptively in the interpolation process according to local property of the image. Application of this function to image enlargement, rotation, and curve representation producted good results. Even in the presence of noise, noise smoothing effect as well as edge-enhancement were observed in the image interpolation process.