image restoration


On this page, we present image restoration results of our own developed technique, compared with standard methods for image restoration. The method we propose is a hybrid method based on steerable pyramids for noise reduction and blur estimaion (our method doesn't require knowledge about the Point Spread Function or PSF) and the Richardson-Lucy (RL) deconvolution method for deblurring, which we will call SPERRiL (Steerable Pyramid-based Estimation and Regularization of Richardson-Lucy restoration). In SPERRiL, we can choose to apply regularization every iteration, or once every n iterations.

Synthetic Test Image


True synthetic testimage


Blur and Poisson noise)

Unregularized RL

RL + slight postblur

SPERRiL, n = 1

SPERRiL, n = 3

SPERRiL, n = 8

Real Confocal Image


Raw confocal image

Unregularized RL

RL + slight postblur

SPERRiL, n = 1

SPERRiL, n = 2

SPERRiL, n = 3