Fundamentals of Digital Image Processing - Control of Color Imaging Systems: Analysis and Design - page 81

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

FIGURE 2.47 Low contrast LENA image and its histogram.

0 0.2 0.4 0.6 0.8 1

FIGURE 2.48 Equalized image and its histogram.

2.9 IMAGE RESTORATION
The goal in image restoration is to reconstruct the original image which has been
subjected to degradation and noise [21,22]. It is usually done by compensating for
the image noise and blur, assuming certain degradation models. The closeness of the
restored image to the original image depends on the accuracy of the model and the
availability of the degradation operator and additive noise statistics. Wiener

filtering,
weighted least square, and maximum likelihood are common techniques for image
restoration. Figure 2.49 shows the block diagram of an image degradation and
restoration system.