Title :
Image decorrelation based on the representation by stochastic models
Author :
Grebenshchikov, K.D. ; Spector, A.A.
Author_Institution :
Novosibirsk State Tech. Univ., Russia
Abstract :
In a number of cases many of the image processing tasks require decorrelation, which simplifies or makes possible subsequent processing. The decorrelation technique based on image representation by causal and non-causal stochastic models is proposed. The influence of the procedure both on background, and on the information component of the image is considered. The results of processing by rank detector operating on decorrelated preparation in the task of step edge detection are given
Keywords :
decorrelation; edge detection; image representation; stochastic processes; causal stochastic models; decorrelated preparation; image decorrelation; image representation; information component; noncausal stochastic models; rank detector; step edge detection; stochastic models; Brightness; Decorrelation; Detectors; Filtering; Filters; Image edge detection; Image processing; Layout; Pixel; Stochastic processes;
Conference_Titel :
Microwave Electronics: Measurements, Identification, Application Conference, 2001. MEMIA 2001
Conference_Location :
Novosibirsk
Print_ISBN :
0-7803-6743-X
DOI :
10.1109/MEMIA.2001.982342
