Frequency and noise dependence of the image reconstruction of ground surfaces using the conjugate gradient based algorithm

2001 ◽  
Vol 148 (4) ◽  
pp. 211 ◽  
Author(s):  
Z. Wu
Keyword(s):  
Image Reconstruction ◽  
Conjugate Gradient ◽  
Gradient Based

Inverse Surfacelet Transform for Image Reconstruction With Constrained-Conjugate Gradient Methods

2014 ◽  
Vol 14 (2) ◽  
Author(s):  
Wei Huang ◽  
Yan Wang ◽  
David W. Rosen
Keyword(s):  
Image Reconstruction ◽  
Conjugate Gradient ◽  
Gradient Methods ◽  
Optimization Methods ◽  
Transformation Process ◽  
Geometric Constraints ◽  
Least Square ◽  
Reconstruction Methods ◽  
Gradient Based ◽  
Surfacelet Transform

Image reconstruction is the transformation process from a reduced-order representation to the original image pixel form. In materials characterization, it can be utilized as a method to retrieve material composition information. In our previous work, a surfacelet transform was developed to efficiently represent boundary information in material images with surfacelet coefficients. In this paper, new constrained-conjugate-gradient based image reconstruction methods are proposed as the inverse surfacelet transform. With geometric constraints on boundaries and internal distributions of materials, the proposed methods are able to reconstruct material images from surfacelet coefficients as either lossy or lossless compressions. The results between the proposed and other optimization methods for solving the least-square error inverse problems are compared.

scholarly journals A Penalized Linear and Nonlinear Combined Conjugate Gradient Method for the Reconstruction of Fluorescence Molecular Tomography

2007 ◽  
Vol 2007 ◽  
pp. 1-19 ◽  
Author(s):  
Shang Shang ◽  
Jing Bai ◽  
Xiaolei Song ◽  
Hongkai Wang ◽  
Jaclyn Lau
Keyword(s):  
Conjugate Gradient Method ◽  
Conjugate Gradient ◽  
Gradient Method ◽  
Optimization Problems ◽  
Gradient Methods ◽  
Reconstruction Algorithms ◽  
Fluorescence Molecular Tomography ◽  
Nonlinear Conjugate Gradient Method ◽  
Gradient Based ◽  
Linear And Nonlinear

Conjugate gradient method is verified to be efficient for nonlinear optimization problems of large-dimension data. In this paper, a penalized linear and nonlinear combined conjugate gradient method for the reconstruction of fluorescence molecular tomography (FMT) is presented. The algorithm combines the linear conjugate gradient method and the nonlinear conjugate gradient method together based on a restart strategy, in order to take advantage of the two kinds of conjugate gradient methods and compensate for the disadvantages. A quadratic penalty method is adopted to gain a nonnegative constraint and reduce the illposedness of the problem. Simulation studies show that the presented algorithm is accurate, stable, and fast. It has a better performance than the conventional conjugate gradient-based reconstruction algorithms. It offers an effective approach to reconstruct fluorochrome information for FMT.

Energy- and Area-Efficient Recursive-Conjugate-Gradient-Based MMSE Detector for Massive MIMO Systems

2020 ◽  
Vol 68 ◽  
pp. 573-588 ◽  
Author(s):  
Leibo Liu ◽  
Guiqiang Peng ◽  
Pan Wang ◽  
Sheng Zhou ◽  
Qiushi Wei ◽  
...  
Keyword(s):  
Conjugate Gradient ◽  
Massive Mimo ◽  
Mimo Systems ◽  
Gradient Based ◽  
Mmse Detector ◽  
Area Efficient
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