A key aspect in extracting quantitative information from FMI logs is to segment the FMI image to get images of pores, vugs and fractures. A segmentation method based on the dyadic wavelet transform in 2-D is introduce...A key aspect in extracting quantitative information from FMI logs is to segment the FMI image to get images of pores, vugs and fractures. A segmentation method based on the dyadic wavelet transform in 2-D is introduced in this paper. The first step is to find all the edge pixels of the FMI image using the 2-D wavelet transform. The second step is to calculate a segmentation threshold based on the average value of the edge pixels. Field data processing examples show that sub-images of vugs and fractures can be correctly separated from original FMI data continuously and automatically along the depth axis. The image segmentation lays the foundation for in-situ parameter calculation.展开更多
This paper introduces a robust global nonlinear optimizer—differential evolution(DE),which is a simple evolution algorithm to search for an optimal transformation that makes the best alignment of two sets of feature ...This paper introduces a robust global nonlinear optimizer—differential evolution(DE),which is a simple evolution algorithm to search for an optimal transformation that makes the best alignment of two sets of feature points.To map the problem of matching into the framework of DE,the objective function is proportional to the registration error which is measured by Hausdorff distance,while the parameters of transformation are encoded in floating-point as the functional variables.Three termination criteria are proposed for DE.A simulation of 2-dimensional point sets and a similarity transformation are presented to compare the robustness and convergence properties of DE with genetic algorithm’s (GA).And the registration of an object and its contour model have been demonstrated by using of DE to natural images.展开更多
An adaptive image denosing technique was proposed to achieve the tradeoff between details retain and noises removal. In order to achieve this objective, the contourlet transform was introduced and a new threshold meth...An adaptive image denosing technique was proposed to achieve the tradeoff between details retain and noises removal. In order to achieve this objective, the contourlet transform was introduced and a new threshold method, namely CWinShrink, is presented. It shrinks the contourlet coefficients with adaptive shrinkage factors. The shrinkage factors were calculated with reference to the sum of squares of the contourlet coefficients within the neighborhood window. This approach achieves enhanced results for images those are corrupted with additive Gaussian noise. In numerical comparisons with various methods, for a set of noisy images （the PSNR range fi＇om 10.86dB to 26.91dB） , the presented method outperforms VisuShrink and Wiener filter in terms of the PSNR. Experiments also show that this method not only keeps the details of image but also yields denoised images with better visual quality.展开更多
A method combining eigenface with different wavelet subbands for face recognition is proposed.Each training image is decomposed into multi-subbands for extracting their eigenvector sets and projection vectors.In the r...A method combining eigenface with different wavelet subbands for face recognition is proposed.Each training image is decomposed into multi-subbands for extracting their eigenvector sets and projection vectors.In the recognition process,the inner product distance between the projection vectors of the test image and that of the training image are calculated.The training image,corresponding to the maximum distance under the given threshold condition,is considered as the final result.The experimental results on the ORL and YALE face database show that,compared with the eigenface method directly on the image domain or on a single wavelet subband,the recognition accuracy using the proposed method is improved by 5% without influencing the recognition speed.展开更多
A simple and practical method to calculate the fractal dimension （FD） of amicron＇s projective surface profile based on fractal theory is proposed. Taking AI（OH）3 material particles as an example, the scanning ele...A simple and practical method to calculate the fractal dimension （FD） of amicron＇s projective surface profile based on fractal theory is proposed. Taking AI（OH）3 material particles as an example, the scanning electron microscope （SEM） photos of particles were processed using an image.processing software （IPS） Photoshop. Taking the pixel as a fixed yardstick with the enlargement of the size of the particle image, the box-dimension and circumference-area （C-S） methods were used to calculate the FD of the surface profile of the particle. The FD of 1.2623 of the classic Koch curve is obtained, which approximates the true value of 1.2628. The complexities of the object＇s boundary and surface micro-topography are simulated successfully by a generator method.展开更多
基金The research was supported by the FifteenthNational Scientific and Technological Project (2001-BA605A-03-02)
文摘A key aspect in extracting quantitative information from FMI logs is to segment the FMI image to get images of pores, vugs and fractures. A segmentation method based on the dyadic wavelet transform in 2-D is introduced in this paper. The first step is to find all the edge pixels of the FMI image using the 2-D wavelet transform. The second step is to calculate a segmentation threshold based on the average value of the edge pixels. Field data processing examples show that sub-images of vugs and fractures can be correctly separated from original FMI data continuously and automatically along the depth axis. The image segmentation lays the foundation for in-situ parameter calculation.
文摘This paper introduces a robust global nonlinear optimizer—differential evolution(DE),which is a simple evolution algorithm to search for an optimal transformation that makes the best alignment of two sets of feature points.To map the problem of matching into the framework of DE,the objective function is proportional to the registration error which is measured by Hausdorff distance,while the parameters of transformation are encoded in floating-point as the functional variables.Three termination criteria are proposed for DE.A simulation of 2-dimensional point sets and a similarity transformation are presented to compare the robustness and convergence properties of DE with genetic algorithm’s (GA).And the registration of an object and its contour model have been demonstrated by using of DE to natural images.
基金Sponsored by Key Lab of Optoelectronic Technology &System,Department of Education, China(Grant No.200373 -1 -2).
文摘An adaptive image denosing technique was proposed to achieve the tradeoff between details retain and noises removal. In order to achieve this objective, the contourlet transform was introduced and a new threshold method, namely CWinShrink, is presented. It shrinks the contourlet coefficients with adaptive shrinkage factors. The shrinkage factors were calculated with reference to the sum of squares of the contourlet coefficients within the neighborhood window. This approach achieves enhanced results for images those are corrupted with additive Gaussian noise. In numerical comparisons with various methods, for a set of noisy images （the PSNR range fi＇om 10.86dB to 26.91dB） , the presented method outperforms VisuShrink and Wiener filter in terms of the PSNR. Experiments also show that this method not only keeps the details of image but also yields denoised images with better visual quality.
基金Supported by Shanghai Science and Technology DevelopmentFoundation (04D02-1)
文摘A method combining eigenface with different wavelet subbands for face recognition is proposed.Each training image is decomposed into multi-subbands for extracting their eigenvector sets and projection vectors.In the recognition process,the inner product distance between the projection vectors of the test image and that of the training image are calculated.The training image,corresponding to the maximum distance under the given threshold condition,is considered as the final result.The experimental results on the ORL and YALE face database show that,compared with the eigenface method directly on the image domain or on a single wavelet subband,the recognition accuracy using the proposed method is improved by 5% without influencing the recognition speed.
基金Project 50474003 supported by the National Natural Science Foundation of China
文摘A simple and practical method to calculate the fractal dimension （FD） of amicron＇s projective surface profile based on fractal theory is proposed. Taking AI（OH）3 material particles as an example, the scanning electron microscope （SEM） photos of particles were processed using an image.processing software （IPS） Photoshop. Taking the pixel as a fixed yardstick with the enlargement of the size of the particle image, the box-dimension and circumference-area （C-S） methods were used to calculate the FD of the surface profile of the particle. The FD of 1.2623 of the classic Koch curve is obtained, which approximates the true value of 1.2628. The complexities of the object＇s boundary and surface micro-topography are simulated successfully by a generator method.
