2. Basic of Image Reconstruction (2): Fundamentals of Iterative Method

2014 ◽  
Vol 70 (4) ◽  
pp. 406-415
Author(s):  
Hiroyuki Shinohara
Keyword(s):  
Image Reconstruction ◽  
Iterative Method

scholarly journals IMAGE RECONSTRUCTION WITH IMPROVED SUPER-RESOLUTION ALGORITHM

2004 ◽  
Vol 18 (08) ◽  
pp. 1513-1527
Author(s):  
CHIEN-YU CHEN ◽  
YU-CHUAN KUO ◽  
CHIOU-SHANN FUH
Keyword(s):  
High Resolution ◽  
Image Reconstruction ◽  
Image Registration ◽  
Iterative Method ◽  
Image Enhancement ◽  
Super Resolution ◽  
Post Processing ◽  
High Resolution Images ◽  
Robust Image ◽  
Resolution Algorithm

In this paper we propose a technique that reconstructs high-resolution images with improved super-resolution algorithms, based on Irani and Peleg iterative method, and employs our suggested initial interpolation, robust image registration, automatic image selection and image enhancement post-processing. When the target of reconstruction is a moving object with respect to a stationary camera, high-resolution images can still be reconstructed, whereas previous systems only work well when we move the camera and the displacement of the whole scene is the same.

Fast Iterative Solving Method of Various Types of Fuzzy Relational Equations and its Application to Image Reconstruction

2001 ◽  
Vol 5 (2) ◽  
pp. 90-98 ◽  
Author(s):  
Hajime Nobuhara ◽  
◽  
Yasufumi Takama ◽  
Kaoru Hirota
Keyword(s):  
Image Reconstruction ◽  
Root Mean Square Error ◽  
Iterative Method ◽  
Computation Time ◽  
Compression Rate ◽  
Reconstruction Method ◽  
Mean Square ◽  
Comparison Process ◽  
Fuzzy Relational Equations ◽  
Image Reconstruction Method

A fast iterative solving method of various types of fuzzy relational equations is proposed. This method is derived by eliminating a redundant comparison process in the conventional iterative solving method (Pedrycz, 1983). The proposed method is applied to image reconstruction, and confirmed that the computation time is decreased to 1/39 - 1/45 with the compression rate of 0.0625. Furthermore, in order to make any initial solution converge on a reconstructed image with good quality, a new cost function is proposed. Under the condition that the compression rate is 0.0625, it is confirmed that the root mean square error of the proposed method decreases to 24.00% and 86.03% compared with those of the conventional iterative method and a non iterative image reconstruction method (Nobuhara, 2001), respectively.

Sign in / Sign up

Export Citation Format

Share Document