Quality Measurement of Blurred Images Using NMSE and SSIM Metrics in HSV and RGB Color Spaces

Quality Measurement of Blurred Images Using NMSE and SSIM Metrics in HSV and RGB Color Spaces Ahmed Majeed Hameed* , Moaz H. Ali, Ramla Abdulnabi Abdulzahra Physics Journal 1, 2, 105-111
Ahmed Majeed Hameed*, Moaz H. Ali, Ramla Abdulnabi Abdulzahra
Al-Safwa University College, Department of Computer Technics, Karbala, Iraq
Abstract
Quality measurement is the process of measuring distortion in images, by using some metrics that makes a comparison between
the original pure image and the distorted image. Image quality measurement is important and helpful for many applications such
as in medicine and space images because images can be affected with many factors of distortions. It is used the Normalize Mean
Square Error (NMSE) and the Structural Similarity Index Measurement (SSIM) as a metric to measure the quality of distorted
images. Gaussian blurring is the type of distortion which is used, so this distortion is applied manually on four color images using
Gaussian blurring function. The distortion is applied on images in the red, green, blue (RGB) and Hue, Saturation, Value (HSV)
color spaces. The result is shown that in the (HSV) the achromatic components have been affected strongly by blurring than
chromatic components, but in the (RGB) colors and lightness are affected similarly because of the high interdependence between
lightness and colors in RGB color space. Experimental results show that in HSV color space there is a high separation between
chromatic and achromatic components, where achromatic component has been affected strongly with blur distortion than
chromatic components. Also, results of RGB shows a high correlation between chromatic and achromatic components, where
these components were identically affected with blur distortion.
Keywords
Blurring, NMSE, SSIM, HSV, RGB, Gaussian Blurring, Image Quality
Received: July