Watching a reflection in a glass window, one can often observe a multi-layered image consisting of a front-surface reflection from the glass and a rear-surface reflection through the glass. That multi-layered image is a composition of dual aspects of the same image, resembling a sound reverberation. As described herein, we propose a method to estimate the original reflection image before the layering. First, we model the multi-layered image generation process; then we derive a restoration filter by assuming that the displacement between the multiple reflection images in the single multi-layered image is known. Second, we propose a method to estimate the original image in conjunction with the displacement estimation. The displacement between the reflection images in a single multi-layered image includes scene depth information. Finally, we demonstrate the effectiveness of our proposed method using both synthetic and real multi-layered images.

This paper presents a calibration and rectification method for single-camera range estimation using a single complex image with a transparent plate or a double-sided half-mirror plate, which are collectively called a reflection stereo. The range to an object is obtainable by finding the correspondence on a constraint line in the complex image, which consists of a surface and a rear-surface reflected image in the transparent plate, or also includes a transmitted and internal reflected image through a double-sided half-mirror plate. The range estimation requires extrinsic parameters of the reflection stereo that include the shape and position of the plate and its refraction index. The proposed method assumes that the plate is non-parallel but planar for a local region around the point of interest in the complex image. The method estimates the extrinsic parameters from a set of displacements in the complex images. Experiments using real images demonstrate the effectiveness of the proposed calibration and rectification method along with fine range estimation results.

The appearance of a distant object, when viewed through a telephoto-lens, is often deformed nonuniformly by the influence of hot-air optical turbulence. The deformation is unsteady: an image sequence can include nonuniform movement of the object even if a stationary camera is used for a static object. This study proposes a multi-frame super-resolution reconstruction from such an image sequence. The process consists of the following three stages. In the first stage, an image frame without deformation is estimated from the sequence. However, there is little detailed information about the object. In the second stage, each frame in the sequence is aligned non-rigidly to the estimated image using a non-rigid deformation model. A stable non-rigid registration technique with a B-spline function is also proposed in this study for dealing with a textureless region. In the third stage, a multi-frame super-resolution reconstruction using the non-rigid deformation recovers the detailed information in the frame obtained in the first stage. Experiments using synthetic images demonstrate the accuracy and stability of the proposed non-rigid registration technique. Furthermore, experiments using real sequences underscore the effectiveness of the proposed process.