#UNMIXING COLOR MACHINE MANUAL#
Importantly, using the proposed method, these high-quality results can be generated using only one-tenth of the manual editing time That the quality of our results is superior to any other currently available green-screen keying solution.
#UNMIXING COLOR MACHINE SOFTWARE#
We present comprehensive comparisons with commercial software packages and relevant methods in literature, which show In this paper, we propose a novel green-screen keying method utilizing a new energy minimization-based color unmixing algorithm. We found that - contrary to the common belief in the research community - production-quality green-screen keying is still an unresolved problem with its unique challenges. To comply with the ever-increasing quality requirements of the industry, specialized compositing artists spend countless hours using multiple commercial software tools, while eventually having to resort to manual painting because of the many shortcomings of these tools.ĭue to the sheer amount of manual labor involved in the process, new green-screen keying approaches that produce better keying results with less user interaction are welcome additions to the compositing artist's arsenal.
Some examples of staining normalization can be seen in the figure below. It is based on the method described in 1.
#UNMIXING COLOR MACHINE CODE#
We demonstrate that our soft color segments can easily be exported to familiar image manipulation software packages and used to produce compelling results for numerous image manipulation applications without forcing the user to learn new tools and workflows.ĭue to the widespread use of compositing in contemporary feature films, green-screen keying has become an essential part of post-production workflows. This MATLAB code performs staining unmixing (separation of the hematoxylin and eosing stains) and apperance normalization. We show that our technique is superior in quality compared to previous methods through quantitative analysis as well as visually through an extensive set of examples. This results in a novel framework for automatic and high-quality soft color segmentation, which is efficient, parallelizable, and scalable. We propose an energy formulation for producing compact layers of homogeneous colors and a color refinement procedure, as well as a method for automatically estimating a statistical color model from an image. We identify a set of requirements that soft color segmentation methods have to fulfill, and present an in-depth theoretical analysis of prior work. We show that the resulting decomposition serves as an effective intermediate image representation, which can be utilized for performing various, seemingly unrelated image manipulation tasks. We present a new method for decomposing an image into a set of soft color segments, which are analogous to color layers with alpha channels that have been commonly utilized in modern image manipulation software.
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