A Deeper Look into Hybrid Images
This is an incremental study for researchers in computer vision and image processing, focusing on refining existing hybrid image techniques.
The paper tackles the problem of understanding how parameter changes affect hybrid image quality by reviewing and tweaking the original method, resulting in an exhaustive study using different images and filters to assess real-time applicability.
$Hybrid$ $images$ was first introduced by Olivia et al., that produced static images with two interpretations such that the images changes as a function of viewing distance. Hybrid images are built by studying human processing of multiscale images and are motivated by masking studies in visual perception. The first introduction of hybrid images showed that two images can be blend together with a high pass filter and a low pass filter in such a way that when the blended image is viewed from a distance, the high pass filter fades away and the low pass filter becomes prominent. Our main aim here is to study and review the original paper by changing and tweaking certain parameters to see how they affect the quality of the blended image produced. We have used exhaustively different set of images and filters to see how they function and whether this can be used in a real time system or not.