Title :
Statistics of Stochastic Textures: Application in pattern analysis and image processing
Author :
Zachevsky, Ido ; Zeevi, Yehoshua Y.
Author_Institution :
Dept. of Electr. Eng., Technion - Israel Inst. of Technol., Haifa, Israel
Abstract :
Unlike the well-established fact of non-Gaussian, highly kurtotic, statistical property that characterizes the general class of natural images, a wide class of Natural Stochastic Textures (NST) obeys, to a good approximation, Gaussianity. This is exploited in denoising, resolution enhancement, analysis, modelling and classification of textures and textured images. Denoising is performed by decomposition to cartoon and textural layers. A fractal model is used to restore the latter. Deconvolution is performed via a variational scheme in the frequency domain, using phase and long-range dependency properties of NST.
Keywords :
frequency-domain analysis; image classification; image denoising; image enhancement; image resolution; image texture; stochastic processes; NST; fractal model; frequency domain; image denoising; image processing; natural stochastic textures; pattern analysis; resolution enhancement; textural layers; texture classification; textured images; variational scheme; Fractals; Gaussian distribution; Image restoration; Noise; Noise measurement; Noise reduction; Stochastic processes;
Conference_Titel :
Electrical & Electronics Engineers in Israel (IEEEI), 2014 IEEE 28th Convention of
Conference_Location :
Eilat
Print_ISBN :
978-1-4799-5987-7
DOI :
10.1109/EEEI.2014.7005899
