An Automatic Restoration Framework for Image Enhancement

An automatic restoration system targeting on dirt and blotches in images has crucial challenges in the aspect of achieving accuracy in Defect Detection and Removal process. Algorithms developed till date suffer from many false alarms and need two stage false alarm elimination process and also limit the expressiveness of the images and only crudely capture the statistics of natural images. The proposed system poses remedies for problems associated with the existing systems. In general, an automatic restoration system contains two stages named as detection of defects and removal of degraded pixels. Adaptive histogram shape based thresholding algorithm is used for creating defect map for finding the degraded pixel which ensures that there will be no false alarm generation. Next, the quality of degraded pixels will be enhanced by using Field of Experts method. This process preserves the expressiveness of the original images and exactly captures the statistics of natural images. The performance will be measured by computing the quality measures such as PSNR and MSE. Finally, experiment results show that the proposed algorithm guarantees the accuracy and efficiency of defect detection and removal processing.