• Khan Bahadar Khan Department of Telecommunication Engineering (UCET), The Islamia University Bahawalpur
  • Muhammad Shahid Al-Khwarizmi Institute of Computer Science, UET Lahore, Pakistan
  • Hayat Ullah International Islamic University Islamabad, Pakistan
  • Eid Rehman Department of Computer Science & Software Engineering, International Islamic University,,Islamabad 44000, Pakistan
  • Muhammad Mohsin Khan International Islamic University Islamabad, Pakistan



A 2-D Adaptive Trimmed Mean Autoregressive (ATMAR) model has been proposed for denoising of medical images corrupted with poisson noise. Unfiltered images are divided into smaller chunks and ATMAR model is applied on each chunk separately. In this paper, two 5x5 windows with 40% overlapping are used to predict the center pixel value of the central row. The AR coefficients are updated by sliding both windows forward with 60% shift. The same process is repeated to scan the entire image for prediction of a new denoised image. The Adaptive Trimmed Mean Filter (ATMF) eradicates the lowest and highest variations in pixel values of the ATMAR model denoised image and also average out the remaining neighborhood pixel values. Finally, power-law transformation is applied on the resultant image of the ATMAR model for contrast stretching. Image quality is judged in terms of correlation, Mean Squared Error (MSE), Structural Similarity Index Measure (SSIM) and Peak Signal to Noise Ratio (PSNR) of the image with latest denoising techniques. The proposed technique showed an efficient way to scale down poisson noise in scintigraphic images on a pixel-by-pixel basis.


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Author Biography

Khan Bahadar Khan, Department of Telecommunication Engineering (UCET), The Islamia University Bahawalpur

Depertment of Electronic Engineering


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How to Cite

Khan, K. B., Shahid, M., Ullah, H., Rehman, E., & Khan, M. M. (2018). ADAPTIVE TRIMMED MEAN AUTOREGRESSIVE MODEL FOR REDUCTION OF POISSON NOISE IN SCINTIGRAPHIC IMAGES. IIUM Engineering Journal, 19(2), 68–79.



Electrical, Computer and Communications Engineering

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