Title :
Image restoration by convex projections using adaptive constraints and the L1 norm
Author :
Kuo, Shyh-shiaw ; Mammone, Richard J.
Author_Institution :
AT&T Bell Lab., Murray Hill, NJ, USA
fDate :
1/1/1992 12:00:00 AM
Abstract :
A new projection method based on the row action projection (RAP) algorithm for image restoration is presented. The new implementation is computationally attractive and facilitates local adaption of projection operators. The local mean and the least L1 norm set of solutions are used as constraints. Computer simulations illustrate the new methods to be very competitive in restoring missing spectral components of a degraded image
Keywords :
picture processing; L1 norm; adaptive constraints; computer simulations; convex projections; image restoration; local mean; row action projection algorithm; spectral components restoration; Additive noise; Application software; Computer simulation; Convolution; Degradation; Helium; Image restoration; Integral equations; Iterative algorithms; Signal processing algorithms;
Journal_Title :
Signal Processing, IEEE Transactions on
