A novel image quality index using Moran I statistics.
Measurement of image quality is very important for various applications such as image compression, restoration and enhancement. Conventional methods (e.g., mean squared error; MSE) use error summation to measure quality change pixel by pixel and do not correlate well with subjective quality measurement. This is due to the fact that human eyes extract structural information from the viewing field. In this study a new quality index using a Moran I statistics is proposed. The Moran statistic that measures the sharpness from a local area is a good index of quality as most image processing techniques alter the smoothness of the image. Preliminary results show that the new quality index outperforms the MSE significantly under various types of image distortions.
Chen
Tzong-Jer
TJ
Department of Nuclear Science, National Tsing-Hua University, Taiwan.
Chuang
Keh-Shih
KS
Wu
Jay
J
Chen
Sharon C
SC
Hwang
Ing-Ming
IM
Jan
Meei-Ling
ML
D000465:Algorithms; D003198:Computer Simulation; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods* / Q000592:standards*; D008279:Magnetic Resonance Imaging; D015233:Models, Statistical; D010781:Photography; D011786:Quality Control