Image gradient L0-norm based PICCS for swinging multi-source CT reconstruction
نویسندگان
چکیده
منابع مشابه
Image reconstruction from few views by L0-norm optimization
In the medical computer tomography (CT) field, total variation (TV), which is the 1 -norm of the discrete gradient transform (DGT), is widely used as regularization based on the comprehensive sensing (CS) theory. To overcome the TV model’s disadvantageous tendency of uniformly penalize the image gradient and over smooth the low-contrast structures, an iterative algorithm based on the 0 -nor...
متن کاملLow-dose spectral CT reconstruction using L0 image gradient and tensor dictionary
Weiwen Wu1,2, Yanbo Zhang2, Qian Wang2, Fenglin Liu1,3,*, Peijun Chen1 and Hengyong Yu2,* 1Key Lab of Optoelectronic Technology and Systems, Ministry of Education, Chongqing University, Chongqing 400044, China 2Department of Electrical and Computer Engineering, University of Massachusetts Lowell, Lowell, MA 01854, USA 3Engineering Research Center of Industrial Computed Tomography Nondestructive...
متن کاملAccelerated gradient methods for total-variation-based CT image reconstruction
Total-variation (TV)-based CT image reconstruction has shown experimentally to be capable of producing accurate reconstructions from sparse-view data. In particular TV-based reconstruction is very well suited for images with piecewise nearly constant regions. Computationally, however, TV-based reconstruction is much more demanding, especially for 3D imaging, and the reconstruction from clinical...
متن کاملImage Reconstruction of Compressed Sensing Based on Improved Smoothed l0 Norm Algorithm
This paper investigates the problem of image reconstruction of compressed sensing. First, an improved smoothed l0 norm (ISL0) algorithm is proposed by using modified Newton method to improve the convergence speed and accuracy of classical smoothed l0 norm (SL0) algorithm, and to increase calculation speed and efficiency. The choice of algorithm parameter is discussed and the algorithm convergen...
متن کاملThe l0-norm-based Blind Image Deconvolution: Comparison and Inspiration
Single image blind deblurring has been intensively studied since Fergus et al.’s variational Bayes method in 2006. It is now commonly believed that the blurkernel estimation accuracy is highly dependent on the pursed salient edge information from the blurred image, which stimulates numerous l0-approximating blind deblurring methods via kinds of techniques and tricks. This paper, however, focuse...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Optics Express
سال: 2019
ISSN: 1094-4087
DOI: 10.1364/oe.27.005264