# Novel Image State Ensemble Decomposition Method for M87 Imaging
## 1 Introduction  
There is need to provide a highly tunable fundamental image processing technique that can remove unwanted color, biased glare, and noise; reduce image artifacts; and improve the contrast and aesthetics in a post-processed RGB image. Generally, one has two main paths to follow when applying image decomposition or enhancement. One typically chooses to be in either the spatial domain or the frequency domain. The image state ensemble decomposition method (ISED) uses sets of spatial domain filters that decompose an image by selectively removing discrete state ensembles from the original image in a red, green, and blue (RGB) color space. This removed portion of the image contains a range of color information that encompasses regions of the image with noise that may biased to a certain domain of the image. These regions may also contain unwanted artifacts and glare. ISED generates images to help discover these biased regions and reduces the unwanted characteristics from the image. ISED generates possible image outcomes from the information contained within a post-processed RGB image. Additionally, ISED is a novel approach that is applicable in many fields; astronomical imaging was chosen out of personal interest. In the spatial domain, direct manipulation of the pixels is normally modified by averaging, median filtering, contrast stretching, Gaussian blurring, many types of histogram equalizations (HE), and the Retinex algorithm, just to name a few [1; 2; 3; 4]. These methods suffer from major drawbacks where the pixel information is either blurred, redistributed, or the intensity is scaled in an unrealistic way [1; 3]. ISED is an image decomposition method that has the ability to remove unwanted color and biased glare,reduce noise, improve contrast, reduce image artifacts, and improve the aesthetics in a post-processed RGB image. ISED retains all of the photonic information from the original information if one simply recombines the ISED image and the ISED filter; provided that the image is saved in a lossless format such as tagged image file (TIF) or PNG, one would have the original image with a structural similarity index (SSIM) equal to 1. Therefore, the process is fully reversible, and the information can be conserved. This is unlike the aforementioned conventional image processing methods, which in essence have a loss or distortion of pixel information. However, the standard image processing techniques are very useful in a case-by-case basis, such as using the median filter to clean salt and pepper noise, using an averaging filter to reduce random statistical noise, and using some form of histogram equalizations (HE) or Retinex to redistribute pixel information to enhance contrast [1; 2]. With ISED, you can be more selective about the informative structures that you wish to study and can extract features in a way that does not corrupt the information in the image. It creates classes of possible filters and possible images, while preserving information, which is dissimilar to existing methods. ISED provides details of structures previously not seen in the images processed by NASA (The National Aeronautics and Space Administration), JPL-Caltech (Jet Propulsion Laboratory, California Institute of Technology), and IPAC (Infrared Processing and Analysis Center). ISED is able to maintain the information of the selected image and move portions of the image to the filter. Thus, there is no loss of pixel information if both the image and filter are known. Therefore, there is no loss of entropy when the ISED filter is recombined with the filtered ISED image: you obtain the original image. With ISED, one can simply generate many possible images from the original image, and as a result of this study, ISED has the ability to show features of galactic structures that were previously hidden within the initial image. Therefore, the need and the purpose of the specific example studied in this paper is to reveal new visual information about M87's galactic structure.