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A method was developed to restore degraded images to some extent after the pixel binning pro-cess in image sensors to improve the resolution. A pixel binning model was used to approximate the original un-binned image. Then, the least squares error criterion was used as a constraint to reconstruct the re-stored pixel values from the binning model. The technique achieves about a one-decibel increase in the peak signal-to-noise ratio compared with the original estimated image. The technique has good detail pre-servation performance as well as low computation load. Thus, this restoration technique provides valuable improvements in practical, real time image processing.
A method was developed to restore degraded images to some extent after the pixel binning pro-cess in image sensors to improve the resolution. A pixel binning model was used to approximate the original un-binned image. Then, the least squares error criterion was used as a constraint to reconstruct the re-stored pixel values from the binning model. The technique achieves about a one-decibel increase in the peak signal-to-noise ratio compared with the original estimated image. The technique has good detail pre-servation performance as well as low computation load. Thus, this restoration technique may valuable improvements in practical, real time image processing.