Comparison of Different Image Enhancing Techniques for Medical Thermal Images

Abstract

Medical infrared (IR) images are, like other medical images, sensitive to noise, which affects directly the temperature measurement of the subject. There are several noise removal techniques that have good performance on digital images, but may produce different temperature readings on thermal images. Hundred and twenty different noisy images were selected from a database and after being processed with several noise removal techniques, the result was statistically analyzed using the standard parameters: maximum, minimum and mean temperature, standard deviation of same region of interest, root mean square error, signal to noise ratio, cross correlation coefficient. In the end, all techniques were compared and graded according with the results. This investigation shows that all techniques produce different results, the recommended method for improving medical thermal images are the Median, Mean and Wiener filters. Results however suggest that noise filtering should only be applied when specifically needed.