Multi-resolution image analysis based on singular value decomposition and subdivision

Author(s):  
Guo Xian Jiu ◽  
Zhang Guo Sheng
2019 ◽  
Vol 90 (3) ◽  
pp. 284-293
Author(s):  
Keita Kawasugi ◽  
Kazuhisa Takemura ◽  
Yumi Iwamitsu ◽  
Hitomi Sugawara ◽  
Sakura Nishizawa ◽  
...  

2015 ◽  
Vol 65 (6) ◽  
pp. 459 ◽  
Author(s):  
K. Joseph Abraham Sundar ◽  
V. Vaithiyanathan ◽  
M. Manickavasagam ◽  
A.K. Sarkar

<p>The singular value decomposition (SVD) plays a very important role in the field of image processing for applications such as feature extraction, image compression, etc. The main objective is to enhance the resolution of the image based on Singular Value Decomposition. The original image and the subsequent sub-pixel shifted image, subjected to image registration is transferred to SVD domain. An enhanced method of choosing the singular values from the SVD domain images to reconstruct a high resolution image using fusion techniques is proposesed. This technique is called as enhanced SVD based fusion. Significant improvement in the performance is observed by applying enhanced SVD method preceding the various interpolation methods which are incorporated. The technique has high advantage and computationally fast which is most needed for satellite imaging, high definition television broadcasting, medical imaging diagnosis, military surveillance, remote sensing etc.</p>


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