Practical quantitative assessment of imaging system in turbid water using a modified fidelity index

Images associated with Underwater Imaging Systems are frequently degraded due to absorption and scattering effects from its underwater environment. The absorption effect reduces the signal strength, and the latter effect reduces both signal strength and image resolution. The optimization of underwater imaging system parameters predominantly focuses on maximizing signal strength and minimizes scattering effects. In the domain of underwater images, the assessment of image quality is highly subjective and lacks the availability of a "standard" objective criteria, which allows a comparison of different imaging techniques and their effectiveness to be performed in a more objective manner. This paper focuses on an experimental performance evaluation of underwater imaging system through objective image quality measurement. The technique is based on 2 dimensional grayscale image of USAF (United State Air Force) target. These targets have been used extensively in underwater imaging system development. It has resolution bars in various frequencies and arrangement, which enable spatial frequencies and signal strength analysis. 3 different image evaluation techniques are used to quantify image quality of an Underwater Imaging System in increased turbidity condition. Peak Signal to Noise Ratio (PSNR) measures the output signal over its Mean Square Error (MSE). Fidelity, F, represents the absolute difference of amplitude values and the Correlation coefficient, r, reflects only changes of signal shape. The metrics scales are considered as a measure of similarity between the idealized and the derived image. In these techniques, the indices are applied to corresponding pixels of the derived and ideal images. The fidelity, F and correlation coefficient, r are applied to thermal imaging evaluation by Volodymyr Borovytsky and Valery Fesenko in 2000. The underwater images have similar characteristics to that from thermal imaging system. There is a significant component of random noise effects (from background or environments) degrading the original signal to be captured by the camera. Test conditions and processes may also induce unwanted errors or distortions into the measurement of the image quality. These include camera movement, light intensity and lens zoom. The sensitivity of some of these effects on the indexes are also presented. Some modifications of the evaluation techniques are proposed. The Modified Fidelity, MF is linearly correlated with the image quality (scattering effects) of the testing images compared to the other methods. Hence, MF is a suitable measure to quantify the scattering effect of underwater images.