Embedded polarizing filters to separate diffuse and specular reflection
This addresses the need for efficient reflection separation in computer vision applications, but it is incremental as it builds on existing camera designs and methods.
The paper tackled the problem of separating diffuse and specular reflection in images by proposing an algorithm for demosaicing images from cameras with embedded polarizing micro-filters, enabling single-image separation and demonstrating normal recovery from estimated diffuse images.
Polarizing filters provide a powerful way to separate diffuse and specular reflection; however, traditional methods rely on several captures and require proper alignment of the filters. Recently, camera manufacturers have proposed to embed polarizing micro-filters in front of the sensor, creating a mosaic of pixels with different polarizations. In this paper, we investigate the advantages of such camera designs. In particular, we consider different design patterns for the filter arrays and propose an algorithm to demosaic an image generated by such cameras. This essentially allows us to separate the diffuse and specular components using a single image. The performance of our algorithm is compared with a color-based method using synthetic and real data. Finally, we demonstrate how we can recover the normals of a scene using the diffuse images estimated by our method.