Title :
A blind image restoration method based on the genetic algorithm and the fuzzy control
Author :
Deng, Li ; Lu, Ruihua
Author_Institution :
Sch. of Electron. & Inf. Eng., Southwest Univ., Chongqing
Abstract :
A blind image restoration method based on the genetic algorithm (GA) and the fuzzy control (FC) is proposed for the situation that the type of the space-variant point spread function (PSF) is unknown and the additive noise is serious. The image is divided into blocks by the triangle meshes. The standard genetic algorithm (SGA) and the micro-population genetic algorithm (micro-PGA) are used alternately to estimate the PSFs and their corresponding image blocks, respectively. At the end of each evolutionary generation of SGA, the best estimated PSF is corrected by the parametric models through FC, so does the best estimated image block according to the histogram statistics after each iteration of micro-PGA. Experiment results show that the presented method can restore the space variant blurred images effectively, and its power of suppressing noise is strong also.
Keywords :
fuzzy control; genetic algorithms; image restoration; statistical analysis; additive noise; blind image restoration method; evolutionary generation; fuzzy control; image block estimation; micropopulation genetic algorithm; noise suppression; space-variant point spread function; standard genetic algorithm; triangle meshes; Additive noise; Degradation; Fuzzy control; Gaussian processes; Genetic algorithms; Genetic engineering; Histograms; Image restoration; Parametric statistics; Signal processing;
Conference_Titel :
Audio, Language and Image Processing, 2008. ICALIP 2008. International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-1723-0
Electronic_ISBN :
978-1-4244-1724-7
DOI :
10.1109/ICALIP.2008.4590046