Image re-ranking is an effective way for improving the result of web-based image search. To refine the text-based image search result image search re-ranking is the best approach. In this Paper, we give the different methods of image re-ranking such as Query Specific Semantic Signature, Graph Based Learning, One Click Internet Image Search and Multimodal Sparse Coding For Click Prediction. And then we propose the One Click Internet Image Search, it requires the user to give only one click on a query image and images from a pool retrieved by text based search are re-ranked based on their visual and textual similarities to the query image. Adaptive similarity, Keyword Expansion, Image pool Image, Visual query expansion by using these four steps we have srearch and re-ranked the images.
