CCD noise removal in digital images.
In this work, we propose a denoising scheme to restore images degraded by CCD noise. The CCD noise model, measured in the space of incident light values (light space), is a combination of signal-independent and signal-dependent noise terms. This model becomes more complex in image brightness space (normal camera output) due to the nonlinearity of the camera response function that transforms incoming data from light space to image space. We develop two adaptive restoration techniques, both accounting for this nonlinearity. One operates in light space, where the relationship between the incident light and light space values is linear, while the second method uses the transformed noise model to operate in image space. Both techniques apply multiple adaptive filters and merge their outputs to give the final restored image. Experimental results suggest that light space denoising is more efficient, since it enables the design of a simpler filter implementation. Results are given for real images with synthetic noise added, and for images with real noise.
Faraji
Hilda
H
Department of Electrical and Computer Engineering, University of Toronto, Toronto, ON M5S 3G4, Canada. hilda@eecg.toronto.edu
MacLean
W James
WJ
D000465:Algorithms; D016477:Artifacts; D003198:Computer Simulation; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D016247:Information Storage and Retrieval / Q000379:methods; D015233:Models, Statistical; D010781:Photography / Q000295:instrumentation / Q000379:methods*; D012815:Signal Processing, Computer-Assisted; D013269:Stochastic Processes