Implementation of A Hybrid Technique using latest category algorithm that joins the Bayesian Network paradigm with the closed Neighbour algorithm

Abstract

For the transmission and enjoyment, Internet is a famous channel. Internet is the collection of huge amount of data like pictures and videos. Large amount of persons click huge amount of pictures and upload and share them with their friends on social media like twitter, facebook etc. Some time huge picture data suffer from many problems like low quality because of compression, imperfect camera, wrong camera target etc. .
Blurriness causes low quality picture, blur is the aspect that reduce the nature of the picture. For high quality picture, blur feature has to be removed. In the area of actual time operation, like satellite transmission to complete the purpose of sending correct data, it is compulsory to enhance the picture quality and also find blur in right way.
In this paper a latest category algorithm that joins the Bayesian Network paradigm with the closed Neighbour algorithm is described. The Bayesian Network shape is gathered from the database in an automatic form with the help of K2 shape learning algorithm. In way to better calculate the classification power of the Bayesian Network approach, user use two distant net evaluation metrics in the information process and make comparison of results gathered by using each of them.