Evaluation image quality for digital image of (cuo) thin films after deblurring and denoise

Author: 
Ziad M. Abood, Khdhier A. Mashjeel and Aya Abdul Kareem Jassim

In this Study, where getting on digital image of (CuO) thin films by using optical microscope and digital camera connected with computer. The objective of this review is to study various filtering technique which is used in image restoring process to reduce the blur, noises and provide the clarity to an image. Where adding different type of noises. Different noises have been considered in this research, and they are: Poisson, Gaussian, salt & pepper, Speckle on the images. De-noising techniques (using MALAB programming) were used to restore the mentioned noises on the images. Different types of filers were used to remove the noises such as Median Filter, Adaptive Wiener Filter and then attempts to undertake the study of restored Motion blurred images by using for types of techniques of deblurring images as Wiener filter, Regularized filter, Lucy-Richardson algorithm, Blind De-convolution algorithm with an information of the point Spread Function (PSF) where they are estimating the causes of the distortion and then apply the restored operations to get the original image. At the final stage, the results of the mentioned filters were compared to get the best and suitable filter for the images of thin films, Image quality parameters (SSIM, FSIM, MSE, SNR RMSE, SNR, and PSNR) were considered as the main parameters for the comparison and showed that there was a clear Enhancement in the lighting and contrast images.

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