中国海区区域地质编图中重磁图的编制方法

本文简要介绍了局控项目《中国海区１：５０万区域地质编图（大连幅）》重力异常图、磁力异常图的编制过程，给出了一种以计算机为手段、实现编图自动化的新方法，并分析了该方法与以往编图方法的不同和优点，以国际分幅在中国海区开展区域地质编图尚属首次，在既无海区地质调查规范，又无海区地质调查编图规范的情况下，这一工作无异具有开创性。从理论上系统总结出一套切实可行的编图方法，对于编制中国海区区域地质调查编图规范以及今后的海区区域地质编图都是非常重要的。

美国区域重、磁异常图的编制与使用

绪言 1975年,几乎与Cocorp计划(大陆地壳深反射剖面协作计划)的同时,美国地学界还开展了一项规模庞大的计划,这就是由SEG与USGS(美国地调所)联合组成全美区域重、磁异常图编制委员会,编制美国及其沿海地区的重、磁异常图。这项工作于1982年基本完成并出版了1:250万重、磁异常图,1985年,SEG还出版了William J.Hinze先生编著的“区域重、磁异常图的使用”一书。由于目前国内尚未全面开展这方面的工作,因此本文就书中提到的编图方法。

Application of Image Enhancement Techniques to Potential Field Data

In this paper the application of image enhancement techniques to potential field data is briefly described and two improved enhancement methods are introduced. One method is derived from the histogram equalization technique and automatically determines the color spectra of geophysical maps. Colors can be properly distributed and visual effects and resolution can be enhanced by the method. The other method is based on the modified Radon transform and gradient calculation and is used to detect and enhance linear features in gravity and magnetic images. The method facilites the detection of line segments in the transform domain. Tests with synthetic images and real data show the methods to be effective in feature enhancement.

Detection of surface cutting defect on magnet using Fourier image reconstruction

A magnet is an important component of a speaker,as it makes the coil move back forth,and it is commonly used in mobile information terminals.Defects may appear on the surface of the magnet while cutting it into smaller slices,and hence,automatic detection of surface cutting defect detection becomes an important task for magnet production.In this work,an image-based detection system for magnet surface defect was constructed,a Fourier image reconstruction based on the magnet surface image processing method was proposed.The Fourier transform was used to get the spectrum image of the magnet image,and the defect was shown as a bright line in it.The Hough transform was used to detect the angle of the bright line,and this line was removed to eliminate the defect from the original gray image;then the inverse Fourier transform was applied to get the background gray image.The defect region was obtained by evaluating the gray-level differences between the original image and the background gray image.Further,the effects of several parameters in this method were studied and the optimized values were obtained.Experiment results show that the proposed method can detect surface cutting defects in a magnet automatically and efficiently.

Two-Level Bregman Method for MRI Reconstruction with Graph Regularized Sparse Coding

In this paper, a two-level Bregman method is presented with graph regularized sparse coding for highly undersampled magnetic resonance image reconstruction. The graph regularized sparse coding is incorporated with the two-level Bregman iterative procedure which enforces the sampled data constraints in the outer level and updates dictionary and sparse representation in the inner level. Graph regularized sparse coding and simple dictionary updating applied in the inner minimization make the proposed algorithm converge with a relatively small number of iterations. Experimental results demonstrate that the proposed algorithm can consistently reconstruct both simulated MR images and real MR data efficiently, and outperforms the current state-of-the-art approaches in terms of visual comparisons and quantitative measures.

Electromagnetic Model and Image Reconstruction Algorithms Based on EIT System

An intuitive 2D model of circular electrical impedance tomography （EIT） sensor with small size electrodes is established based on the theory of analytic functions. The validation of the model is proved using the result from the solution of Laplace equation. Suggestions on to electrode optimization and explanation to the ill-condition property of the sensitivity matrix are provided based on the model, which takes electrode distance into account and can be generalized to the sensor with any simple connected region through a conformal transformation. Image reconstruction algorithms based on the model are implemented to show feasibility of the model using experimental data collected from the EIT system developed in Tianjin University. In the simulation with a human chestlike configuration, electrical conductivity distributions are reconstructed using equi-potential backprojection （EBP） and Tikhonov regularization （TR） based on a conformal transformation of the model. The algorithms based on the model are suitable for online image reconstruction and the reconstructed results are aood both in size and position.