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\begin{document}

\title{Image Processing Results of One Week Covid-19 Evolution Pneumonia X-Rays}



\author[1]{Abhishek Bansal }%
\affil[1]{NOT APPLICABLE}%


\vspace{-1em}



  
  \date{May 19, 2024}


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\begin{abstract}
This paper presents the collection of 385 new images and results,
obtained after performing many known image processing algorithms and
digital image transformations techniques like adding noises namely
Gaussian with variances, Poisson and speckle with variances; double
precision, methods of Sobel, Prewitt and Robert; dehazing algorithm,
pixel intensities, vector quantization, k-means clustering, fuzzy logic
and morphological segmentation. Images used in this paper are five
X-Rays at day 0, day3, day 4 and day 6, which are Posterior to Anterior
(PA) views of the patient's lungs who was diagnosed with covid-19
Pneumonia. All results are included in the paper as well as separate
images have also been uploaded on the open-access page. The data has
been analyzed with histogram and mathematical polynomial fitting
equations and matrices have been also submitted which can used in the
digital testing of machines or computer diagnostic solutions. As these
results reveal certain patterns, these further processed X-Ray results
can help researchers or doctors in understanding ailment or diagnosing
and to pharmacologists in making medicine or machine/therapy.%
\end{abstract}%



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