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In the digital post-production environment, methods exist for eliminating the misregistration outlined above using a manual process.

The pipeline begins with three monochrome digitized frame sequences. For the remainder of this document, these will be referred to as the Red channel (R), the Green channel (G) and the Blue channel (B) respectively.

From within a digital compositing package, each separation frame sequence is first digitally stabilized over time. Typically, this is done using feature-tracking. Next, the first frame of the sequence is recombined manually. The (x, y) offsets of the Red and Blue layers are adjusted so that their image content matches that of the Green layer without any misregistration. The Green layer is designated as the “hero channel”. There seems to be a consensus within the film industry that, for the majority of film stocks, the Green layer exhibits low grain and high luminance content when compared to the Red and Blue layers. This makes the Green layer a good reference. It is kept fixed while the Red and Blue layers are moved around.

Once the first frame has been recombined in this way, those (x, y) offsets are propagated forward to every frame in the sequence. This is intended to correctly reregister all remaining frames. In practice, this only works some of the time. Any inaccuracies in stabilization mean that frames later in the sequence might still be misregistered. Furthermore, each shot in the movie must be tracked separately, since a new set of features must be specified by the compositor each time a shot transition occurs.

At Cinesite, research was undertaken to investigate methods of automating the process of reregistering Red, Green and Blue separations to form color images. Performing the task automatically allows the labor-intensive and error-prone process of manual reregistration described above to be circumvented. This enables major savings in both time and cost in the digital film restoration pipeline.

Section 3 – The New Technique


Automated Reregistration

Again, the starting point is three sets of monochrome digitized frame sequences R, G and B.

A hero-channel is designated as before. Whilst this is typically the Green channel, a different hero-channel can be designated if required. Two independent searches are performed. In the first, the Red channel is deformed to match it to the Green channel as closely as possible. A second search does a similar job to deform the Blue channel to match it to the Green (see Figure 2).

[Figure 2: Steps in recombining three monochrome separations into one color image]

 The problem essentially reduces to two optimizations. This strategy is outlined in the following sections.


Measuring Image Similarity

Consider a similarity measure between two monochrome images A and B, referred to as D(A, B). The following properties are defined for the measure:


Property (1) limits the measure to a real number which is always non-negative.

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