Image Quality Assessment for Image Filtering Algorithm: Qualitative and Quantitative Analyses

This paper will introduce the image quality assessment for image filtering algorithm based on qualitative and quantitative analyses. Image with noise becomes a problem for gaining information. The process begins by improving the image quality by applying various filters that can enhance the image to be subjectively better. The image result can be seen after the image has gone through the enhancement process (image filter) where more detail can be seen, unwanted flickering removed and the image contrast increasingly better. The objective is to find an image filtering algorithm that gives an excellent result based on the image quality assessment. The image quality assessment is the analyses based on the parameter of means square error and peak- signal noise ratio in decibels by using MATLAB software. The image filtering algorithm then uses the median filter, gaussian filter, mean filter and wiener filter. Different noises such as gaussian and salt & pepper are applied with different noise percentage added to the image to determine which image filter has better performance. Last but not least, this paper image quality assessment for the image filtering algorithm through the qualitative and quantitative analyses will discuss the most efficient image filter to remove unwanted signal and noise on the image.