title: Joint demosaicing and denoising.
abstract: The output image of a digital camera is subject to a severe degradation due to noise in the image sensor. This paper proposes a novel technique to combine demosaicing and denoising procedures systematically into a single operation by exploiting their obvious similarities. We first design a filter as if we are optimally estimating a pixel value from a noisy single-color (sensor) image. With additional constraints, we show that the same filter coefficients are appropriate for color filter array interpolation (demosaicing) given noisy sensor data. The proposed technique can combine many existing denoising algorithms with the demosaicing operation. In this paper, a total least squares denoising method is used to demonstrate the concept. The algorithm is tested on color images with pseudorandom noise and on raw sensor data from a real CMOS digital camera that we calibrated. The experimental results confirm that the proposed method suppresses noise (CMOS/CCD image sensor noise model) while effectively interpolating the missing pixel components, demonstrating a significant improvement in image quality when compared to treating demosaicing and denoising problems independently.
authors.affiliation: Cornell University, Ithaca, NY 14853, USA. hirakawa@stat.harvard.edu
authors.forename: Keigo
authors.initials: K
authors.lastname: Hirakawa
authors.forename: Thomas W
authors.initials: TW
authors.lastname: Parks
mesh_terms: D000465:Algorithms; D016477:Artifacts; D003124:Colorimetry / Q000295:instrumentation / Q000379:methods*; D003196:Computer Graphics; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D016247:Information Storage and Retrieval / Q000379:methods; D009716:Numerical Analysis, Computer-Assisted; D012815:Signal Processing, Computer-Assisted; D013382:Subtraction Technique; D014159:Transducers; D014741:Video Recording / Q000295:instrumentation / Q000379:methods*