A ringing metric to evaluate the quality of images restored using iterative deconvolution algorithms

Iterative deconvolution algorithms exhibit increased ringing artifacts at higher number of iterations. Quantitative image analysis techniques such as optical flow algorithms are sensitive to these artifacts. We propose to use an image quality metric to identify the terminal step of iterative restoration algorithms. Frequency based metrics have difficulties in distinguishing the ringing artifacts from the image features. Spatial analysis techniques require extensive processing making them unsuitable for real-time image quality measurement as needed in iterative image restoration. We propose a novel ringing metric using binary morphological operators and demonstrate the method on the images of random cotton fibers acquired using white light confocal microscope.