We present a new representation for image-based interactive walk-throughs. The target applications reconstruct a scene from novel viewpoints using samples from a spatial image dataset collected from a plane at eye-level. These datasets consist of pose augmented 2D images and often have a very large number of samples. Our representation exploits spatial coherence and rearranges the input samples as epipolar images. The base unit corresponds to a column of the original image that can be individually addressed and accessed. The overall representation, IRW, supports incremental updates, efficient encoding, scalable performance, and selective inclusion used by different reconstruction algorithms. We demonstrate the performance of our representation on a synthetic as well as a real-world environment.