Applied Sciences (Feb 2020)

Novel Image State Ensemble Decomposition Method for M87 Imaging

  • Timothy Ryan Taylor,
  • Chun-Tang Chao,
  • Juing-Shian Chiou

DOI
https://doi.org/10.3390/app10041535
Journal volume & issue
Vol. 10, no. 4
p. 1535

Abstract

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This paper proposes a new method of image decomposition with a filtering capability. The image state ensemble decomposition (ISED) method has generative capabilities that work by removing a discrete ensemble of quanta from an image to provide a range of filters and images for a single red, green, and blue (RGB) input image. This method provides an image enhancement because ISED is a spatial domain filter that transforms or eliminates image regions that may have detrimental effects, such as noise, glare, and image artifacts, and it also improves the aesthetics of the image. ISED was used to generate 126 images from two tagged image file (TIF) images of M87 taken by the Spitzer Space Telescope. Analysis of the images used various full and no-reference quality metrics as well as histograms and color clouds. In most instances, the no-reference quality metrics of the generated images were shown to be superior to those of the two original images. Select ISED images yielded previously unknown galactic structures, reduced glare, and enhanced contrast, with good overall performance.

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