Efficient of adaptive filters in image enhancement quality of porous silicon images layers

Recently, several studies have focused on filters to reduce or eliminate speckle noise in Porous Silicon (PS) images, aiming to enhance the metrological assessment of their applications. The objective of this study is to emphasize the significance of enhancing these smoothing and elimination processes, as they are directly linked to multiple procedures, such as the detection of interest regions. Additionally, the description of these techniques facilitates the implementation of evaluations and research with a more specific focus. The study initially addresses the definition and effets of speckle noise, followed by a detailed exploration of statistical parameters such as Signal to Noise Ratio (SNR), Peak Signal to Noise Ratio (PSNR), Structural Similarity Index (SSIM), Mean Square Error (MSE), and Root Mean Square Error (RMSE) .Finally, the results are tabulated where can these parameters provide greater certainty in the classification of the filters by considering their behavioral information in terms of perceptual quality provided by parameter metrics.