• Title/Summary/Keyword: resolution-adaptive

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Boundary stress resolution and its application to adaptive finite element analysis

  • Deng, Jianhui;Zheng, Hong;Ge, Xiurun
    • Structural Engineering and Mechanics
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    • v.6 no.1
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    • pp.115-124
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    • 1998
  • A novel boundary stress resolution method is suggested in this paper, which is based upon the displacements of finite element analysis and of high precision with stress boundary condition strictly satisfied. The method is used to modify the Zienkiewicz-Zhu ($Z^2$) a posteriori error estimator and for the h-version adaptive finite element analysis of crack problems. Successful results are obtained.

Spatially Adaptive Image Fusion Based on Local Spectral Correlation (지역적 스펙트럼 상호유사성에 기반한 공간 적응적 영상 융합)

  • 김성환;박종현;강문기
    • Proceedings of the IEEK Conference
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    • 2003.07e
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    • pp.2343-2346
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    • 2003
  • The spatial resolution of multispectral images can be improved by merging them with higher resolution image data. A fundamental problem frequently occurred in existing fusion processes, is the distortion of spectral information. This paper presents a spatially adaptive image fusion algorithm which produces visually natural images and retains the quality of local spectral information as well. High frequency information of the high resolution image to be inserted to the resampled multispectral images is controlled by adaptive gains to incorporate the difference of local spectral characteristics between the high and the low resolution images into the fusion. Each gain is estimated to minimize the l$_2$-norm of the error between the original and the estimated pixel values defined in a spatially adaptive window of which the weight are proportional to the spectral correlation measurements of the corresponding regions. This method is applied to a set of co-registered Landsat7 ETM+ panchromatic and multispectral image data.

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Adaptive Image Interpolation Using Pixel Embedding (화소 삽입을 이용한 적응적 영상보간)

  • Han, Kyu-Phil;Oh, Gil-Ho
    • Journal of Korea Multimedia Society
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    • v.17 no.12
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    • pp.1393-1401
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    • 2014
  • This paper presents an adaptive image interpolation method using a pixel-based neighbor embedding which is modified from the patch-based neighbor embedding of contemporary super resolution algorithms. Conventional interpolation methods for high resolution detect at least 16-directional edges in order to remove zig-zaging effects and selectively choose the interpolation strategy according to the direction and value of edge. Thus, they require much computation and high complexity. In order to develop a simple interpolation method preserving edge's directional shape, the proposed algorithm adopts the simplest Haar wavelet and suggests a new pixel-based embedding scheme. First, the low-quality image but high resolution, magnified into 1 octave above, is acquired using an adaptive 8-directional interpolation based on the high frequency coefficients of the wavelet transform. Thereafter, the pixel embedding process updates a high resolution pixel of the magnified image with the weighted sum of the best matched pixel value, which is searched at its low resolution image. As the results, the proposed scheme is simple and removes zig-zaging effects without any additional process.

Adaptive Control for the Conventional Mode of Operation of MEMS Gyroscopes

  • Park, Sungsu;Roberto Horowitz
    • 제어로봇시스템학회:학술대회논문집
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    • 2002.10a
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    • pp.39.2-39
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    • 2002
  • This paper presents adaptive add-on control algorithms for theconventional mode of operation of MEMS z-axis gyroscopes. This scheme is realized by adding an outer loop to a conventional force-balancing scheme that includes a parameter estimation algorithm. The parameter adaptation algorithm estimates the angular rate, identifies and compensates the quadrature error, and may permit on-line automatic mode tuning. The convergence and resolution analysis show that the proposed adaptive add-on control scheme prevents the angular rate estimate from being contaminated by the quadrature error, while keeping ideal resolution performance of a conventional force-balancing scheme.

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Super-resolution Microscopy with Adaptive Optics for Volumetric Imaging

  • Park, Sangjun;Min, Cheol Hong;Han, Seokyoung;Choi, Eunjin;Cho, Kyung-Ok;Jang, Hyun-Jong;Kim, Moonseok
    • Current Optics and Photonics
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    • v.6 no.6
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    • pp.550-564
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    • 2022
  • Optical microscopy is a useful tool for study in the biological sciences. With an optical microscope, we can observe the micro world of life such as tissues, cells, and proteins. A fluorescent dye or a fluorescent protein provides an opportunity to mark a specific target in the crowd of biological samples, so that an image of a specific target can be observed by an optical microscope. The optical microscope, however, is constrained in resolution due to diffraction limit. Super-resolution microscopy made a breakthrough with this diffraction limit. Using a super-resolution microscope, many biomolecules are observed beyond the diffraction limit in cells. In the case of volumetric imaging, the super-resolution techniques are only applied to a limited area due to long imaging time, multiple scattering of photons, and sample-induced aberration in deep tissue. In this article, we review recent advances in super-resolution microscopy for volumetric imaging. The super-resolution techniques have been integrated with various modalities, such as a line-scan confocal microscope, a spinning disk confocal microscope, a light sheet microscope, and point spread function engineering. Super-resolution microscopy combined with adaptive optics by compensating for wave distortions is a promising method for deep tissue imaging and biomedical applications.

Array Resolution Improving Methods for Beamforming Algorithm (빔형성방법에서의 분해능 향상 기법에 관한 연구)

  • Hwang, Seon-Gil;Rhee, Wook;Choi, Jong-Soo
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2005.05a
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    • pp.164-169
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    • 2005
  • Microphone array techniques are being used widely in wind tunnel measurements for identification of the distributed aerodynamic noise sources on the model being tested. Depending on the frequencies and sound levels, conventional beamforming algorithm has limitation in separating two adjacent sources. Several modifications to the classical beamforming have been developed to enhance way resolution and reduce sidelobe levels. In this Paper the robust adaptive beamforming and the CLEAN algorithm are used to compare to the result of conventional beamforming method. It is found that the CLEAN algorithm is capable of pin-pointing locations of multiple sources nearby, while these sources are unidentifiable with robust adaptive or conventional beamforming techniques.

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An Efficient Adaptive Wavelet-Collocation Method Using Lifted Interpolating Wavelets (수정된 보간 웨이블렛응 이용한 적응 웨이블렛-콜로케이션 기법)

  • Kim, Yun-Yeong;Kim, Jae-Eun
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.24 no.8 s.179
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    • pp.2100-2107
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    • 2000
  • The wavelet theory is relatively a new development and now acquires popularity and much interest in many areas including mathematics and engineering. This work presents an adaptive wavelet method for a numerical solution of partial differential equations in a collocation sense. Due to the multi-resolution nature of wavelets, an adaptive strategy can be easily realized it is easy to add or delete the wavelet coefficients as resolution levels progress. Typical wavelet-collocation methods use interpolating wavelets having no vanishing moment, but we propose a new wavelet-collocation method on modified interpolating wavelets having 2 vanishing moments. The use of the modified interpolating wavelets obtained by the lifting scheme requires a smaller number of wavelet coefficients as well as a smaller condition number of system matrices. The latter property makes a preconditioned conjugate gradient solver more useful for efficient analysis.

Multi-resolution Lossless Image Compression for Progressive Transmission and Multiple Decoding Using an Enhanced Edge Adaptive Hierarchical Interpolation

  • Biadgie, Yenewondim;Kim, Min-sung;Sohn, Kyung-Ah
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.11 no.12
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    • pp.6017-6037
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    • 2017
  • In a multi-resolution image encoding system, the image is encoded into a single file as a layer of bit streams, and then it is transmitted layer by layer progressively to reduce the transmission time across a low bandwidth connection. This encoding scheme is also suitable for multiple decoders, each with different capabilities ranging from a handheld device to a PC. In our previous work, we proposed an edge adaptive hierarchical interpolation algorithm for multi-resolution image coding system. In this paper, we enhanced its compression efficiency by adding three major components. First, its prediction accuracy is improved using context adaptive error modeling as a feedback. Second, the conditional probability of prediction errors is sharpened by removing the sign redundancy among local prediction errors by applying sign flipping. Third, the conditional probability is sharpened further by reducing the number of distinct error symbols using error remapping function. Experimental results on benchmark data sets reveal that the enhanced algorithm achieves a better compression bit rate than our previous algorithm and other algorithms. It is shown that compression bit rate is much better for images that are rich in directional edges and textures. The enhanced algorithm also shows better rate-distortion performance and visual quality at the intermediate stages of progressive image transmission.

Adaptive MAP High-Resolution Image Reconstruction Algorithm Using Local Statistics (국부 통계 특성을 이용한 적응 MAP 방식의 고해상도 영상 복원 방식)

  • Kim, Kyung-Ho;Song, Won-Seon;Hong, Min-Cheol
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.31 no.12C
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    • pp.1194-1200
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    • 2006
  • In this paper, we propose an adaptive MAP (Maximum A Posteriori) high-resolution image reconstruction algorithm using local statistics. In order to preserve the edge information of an original high-resolution image, a visibility function defined by local statistics of the low-resolution image is incorporated into MAP estimation process, so that the local smoothness is adaptively controlled. The weighted non-quadratic convex functional is defined to obtain the optimal solution that is as close as possible to the original high-resolution image. An iterative algorithm is utilized for obtaining the solution, and the smoothing parameter is updated at each iteration step from the partially reconstructed high-resolution image is required. Experimental results demonstrate the capability of the proposed algorithm.

Adaptive Contrast Stretching for Land Observation in Cloudy Low Resolution Satellite Imagery

  • Lee, Hwa-Seon;Lee, Kyu-Sung
    • Korean Journal of Remote Sensing
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    • v.28 no.3
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    • pp.287-296
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    • 2012
  • Although low spatial resolution satellite images like MODIS and GOCI can be important to observe land surface, it is often difficult to visually interpret the imagery because of the low contrast by prevailing cloud covers. We proposed a simple and adaptive stretching algorithm to enhance image contrast over land areas in cloudy images. The proposed method is basically a linear algorithm that stretches only non-cloud pixels. The adaptive linear stretch method uses two values: the low limit (L) from image statistics and upper limit (U) from low boundary value of cloud pixels. The cloud pixel value was automatically determined by pre-developed empirical function for each spectral band. We used MODIS and GOCI images having various types of cloud distributions and coverage. The adaptive contrast stretching method was evaluated by both visual interpretation and statistical distribution of displayed brightness values.