28-03-2012, 04:54 PM
Image Restoration includes processes
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. INTRODUCTION
Image Restoration includes processes that attempt to remove degradations and restore an Restoration is distinguished from enhancement image to a previous state. Restoration techniques are oriented toward modeling the degradation and applying the inverse process to recover the original image. in that degradation can be considered an external influence that is separate from the image signal. Restoration usually involves formulating a criterion of goodness that will give an optimal estimate of the desired result. Enhancement, on the other hand, usually manipulates with subjective criteria. Contrast stretching is an enhancement while enhancement, removing the image blur when applying a DE blurring function is a restoration. Images are produced to record or display useful information. Due to imperfections in the imaging and capturing process, however, the recorded image invariably represents a degraded version of the original scene. The undoing of these imperfections is crucial to many of the subsequent image processing tasks. There exists a wide range of different degradations, which are to be taken into account, for instance noise, geometrical degradations (pincushion distortion), illumination and color imperfections (under / overexposure, saturation), and blur. Blurring is a form of Bandwidth reduction of an ideal image owing to the imperfect image formation process.
. How it is differ from image enhancement
Image enhancement: “improve” an image subjectively.
Image restoration: remove distortion from image in order to go back to the “original” → objective process
Model of Image Restoration
Capturing an image exactly as it appears in the real world is very difficult if not impossible. In case of photography or imaging systems these are caused by the graininess of the emulsion, motion-blur, and camera focus problems. The result of all these degradations is that the image is an approximation of the original. The above mentioned degradation process can adequately be described by a linear spatial model as shown in Figure The original input is a two-dimensional (2D) image f(x, y). This image is operated on by the system H and after the addition of n(x, y). one can obtain the degraded image g(x,y).
Methods of Restoration
1. Inverse Filtering
2. Wiener Filter De-blurring Technique
3. Constrained least square Filtering
Restore an image that has been degraded in some way.
Make a model of the degeneration process and use inverse methods.
Image restoration is an objective method using a priori information of the degradation.
Conclusion
A method for restoring the images of a suspected person taken by a security camera was proposed base on our proposed concept. In the concept, the peculiar facts concerning the security camera system that all the things in the image except the suspected person itself are usually preserved and that can be used for investigations are to be used as fully as possible. The importance of pursuing the proposed concept was discussed from the viewpoints of not only the novelty in image processing technology but also the viewpoints of the efficiency in criminal investigation and social security.