Journals Proceedings

Abstract

Infrared (IR) imaging helps to capture the images with different temperature range and also captures better quality images during night time. Infrared Thermography is an emerging technology for nondestructive testing. So infrared images are considered to identify and classify ice types of river ice. However, it is subject to blurring and degradation of the acquired signal, as the diffusive nature in the process. This makes difficulties for qualitative and quantitative analyses, especially when deeper defects which are located within the substrate, as well as high thermal conductivity materials are inspected. The IR images usually have noise, edges, text information and small objects of interest. Non linear filters such as standard median filter however often tends to remove fine details in the image, such as thin lines and corners. So to overcome the drawback of median filter, relaxed median filter, adaptive median filter, decision based median filter and untrimmed decision based median filters are used for denoising. The results of all the filters are compared by using peak signal to noise ratio (PSNR) and mean square error (MSE), and found that untrimmed decision based median filter (UDBMF) gives higher results.