Image restoration is the reconstruction of a degraded image towards the original object by the reduction or removal of the degradations. These degradations may be introduced during the formation, transmission and reception of the image. Natural images have distinct features that allow the human visual system to detect the presence of distortion, and to extract remaining information from the observation. Image restoration aims to construct an approximation sharing the relevant features still present in the corrupted image, but with the artifacts suppressed. In order to distinguish the artifacts from the signal, a good image model is essential. Most of the image restoration techniques model the degradation phenomenon, usually blur and noise, and then obtain an approximation of the image. Whereas, in realistic situation, one has to estimate both the true image and the blur from the degraded image characteristics in the absence of any a priori information about the blurring system. In this paper, an automatic system is proposed for detecting the presence of split defects in sheet-metal forming processes.

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Image Restoration Artifacts Degradation model Filters Machine Vision