Title :
Image magnification method using Compressed Sensing
Author :
Shang, Fei ; Du, Hui-Qian
Author_Institution :
Sch. of Life Sci., Beijing Inst. of Technol., Beijing, China
Abstract :
In this paper, a new method for image magnification is presented. The image reduction is seen as a result of image multiplying with a compressed matrix, and the magnification is stated as an inverse problem of reduction. We exploit the reconstruction idea of Compressed Sensing and propose a norm minimization model to solve the inverse problem. The norm reflects the image´s natural property - compressive in transform domain and local smoothness in space domain, its minimization is the magnification result. The experimental results show that the enlarged images produced by the new method have higher precision and hence offer more detail information than traditional methods.
Keywords :
image coding; inverse problems; matrix algebra; compressed matrix; compressed sensing; image magnification; image reduction; inverse problem; norm minimization model; space domain; transform domain; Compressed sensing; Image coding; Image reconstruction; Interpolation; Inverse problems; Minimization; Pixel;
Conference_Titel :
Audio Language and Image Processing (ICALIP), 2010 International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-5856-1
DOI :
10.1109/ICALIP.2010.5684520