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Superresolution Testing and Results

Module by: Jennifer Gillenwater, J. Ryan Stinnett, Elica Skorcheva. E-mail the authors

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Summary: Using projective flow and Delauany triangulation to accompish image registration and interpolation, we achieved the following superresolution results.

The following images illustrate the effects of the projective flow and Delaunay triangulation algorithms we used to implement image superresolution. Our testing process was as follows:

  1. Take several pictures of the same object with a digital camera (no tripod -> images will need registration).
  2. Downsample the images to create low-resolution (LR) copies.
  3. Register all LR images with respect to the first LR image.
  4. Interpolate to obtain the HR image.

We also tested using LR images from external sources. An example is given below.

  • Original images:
    Figure 1: LR image 1 (Source: 7)
    Figure 1 (castle1.png)
    Figure 2: LR image 2 (Source: 7)
    Figure 2 (castle2.png)
    Figure 3: LR image 3 (Source: 7)
    Figure 3 (castle3.png)
    Figure 4: LR image 4 (Source: 7)
    Figure 4 (castle4.png)
  • HR image result:
    Figure 5: HR image
    Figure 5 (resavg.png)

The MATLAB code used to generate the above HR image is available here.

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Definition of a lens

Lenses

A lens is a custom view of Connexions content. You can think of it as a fancy kind of list that will let you see Connexions through the eyes of organizations and people you trust.

What is in a lens?

Lens makers point to Connexions materials (modules and collections), creating a guide that includes their own comments and descriptive tags about the content.

Who can create a lens?

Any individual Connexions member, a community, or a respected organization.

What are tags? tag icon

Tags are descriptors added by lens makers to help label content, attaching a vocabulary that is meaningful in the context of the lens.

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