期刊名称：International Journal of Advanced Research In Computer Science and Software Engineering
印刷版ISSN：2277-6451
电子版ISSN：2277-128X
出版年度：2013
卷号：3
期号：6
出版社：S.S. Mishra
摘要：Digital cameras can only capture a limited dynamic range, when taking a photograph of a scene bright areas tend to be over-exposed while dark regions tend to be under-exposed. These bright and dark regions appear saturated in the image, to enlarge the dynamic ranges panned by conventional cameras a very interesting and power full technique has been developed in the last few years high dynamic range imaging. The obtained images are called high dynamic range (HDR) images, We will use many techniques for fusion these low dynamic images to get high dynamic image here we discussing two methods namely fusion in radiance domain and fusion in image domain. The main limitation of the multiple exposures combination technique is the requirement of a complete static scene when capturing the images. Indeed, any object movement in the scene can cause ghosting artifacts in the resulting HDR image. Here we use four methods to detect the ghosting in HDR image namely Variance based ghost detection, Entropy based ghost detection, Prediction based ghost detection, Pixel order relation, Removing ghosting artifacts in the combined HDR image is the ultimate aim of any method that addresses the ghost problem. Different methods produce different results and can be classified into two main categories. Keeping a single occurrence of moving object, removing all moving objects. Methods that combine exposures in the radiance domain give a true HDR radiance map which might be useful for later processing or display applications, there is no single best method and the selection of an approach depends on the user's goal. For removing all moving objects in the final HDR image, hence further research is required.
