Title :
A combined approach to enhancement of unknown blurred and noisy images
Author_Institution :
Comput. Sci. Lab., Australian Nat. Univ., Canberra, ACT, Australia
Abstract :
Estimating the point-spread function of a real-world blurred image is an essential step in the restoration process. When blur is unknown and the noise varies over the neighborhood, image restoration is more difficult. Unlike the deterministic blur identification techniques that attempt to identify the PSF function, this paper introduces the AADIF, statistical, multidirectional and comparative (ASMC) sharpening approaches for dealing with unknown blurred and noisy images. The results are given to show the effectiveness and the practicality of the ASMC approach
Keywords :
edge detection; filtering and prediction theory; image processing; image reconstruction; statistical analysis; AADIF; comparative sharpening; edge detection; image restoration; multidirectional sharpening; noise filtering; noisy images; point-spread function; real-world blurred image; restoration process; statistical sharpening; Degradation; Filtering; Filters; Frequency; Image edge detection; Image restoration; Image segmentation; Noise figure; Noise level; Signal to noise ratio;
Conference_Titel :
Speech, Image Processing and Neural Networks, 1994. Proceedings, ISSIPNN '94., 1994 International Symposium on
Print_ISBN :
0-7803-1865-X
DOI :
10.1109/SIPNN.1994.344795
