Evaluation of Rich Edge Region Extraction and Prewitt Edge Detection Techniques for Improving the Accuracy of Image Restoration in Motion-Blurred Images

This study is primarily aimed at comparing the % of restored motion blurred photos, using Novel Rich Edge Region Extraction algorithm and Prewitt Edge Detection Technique. This comparison will be made with Novel Rich Edge Region Extraction. There is also a comparative analysis of the models depending on their accuracy and efficiency. Group 1, which has used Novel Rich Edge Region Extraction technique with sample size one hundred; then group two, which uses Prewitt edge detection technic ten times for samples having same fifties using that so method A comparison was made between the efficiency and accuracy of each model with a G-power 0.80 value at alpha= 0. .5(95% CI) The accuracy and performance of each model were analyzed. In accordance with the findings derived from the study investigation, it was found out that Novel Rich Edge Region Extraction achieved an accuracy of 94.43% while Prewitt Edge Detection settled for an accuracy percentage 91-52%. Therefore, independent sample T-test was performed and the results obtained were p=0.000 (p< ð16), Thus showing that there is a statically significant difference If we compare the above-proposed method, Novel Rich Edge Region Extraction giving a score of 94.43%, with Prewitt Edge Detection Technique that gave away with 91.52% to evaluate final results between these two methods. The results showed that the proposed model was more efficient than the current one.