Impulse Noise Detector Performance Measure Based on Intensity Volume

An accurate detector performance evaluation method provides a fair comparison platform and can also support in parameter optimization for existing Impulse noise detectors in the applications of medical imaging. The Impulse noise detector performance measure (INDPM) package is widely applied as tools for quantitative comparison among detectors, which contains recall measure, accuracy measure, precision measure, specificity measure and F-measure. However, these five measures suffer from limited accuracy in correctly evaluating the performance of a detector and are not in well agreement with human subjective evaluation. To solve this problem, five new measures are proposed by introducing a new concept of intensity volume to form a new Impulse noise detector performance package (IV-INDPM). Using a standard image dataset, we conduct experimental and comparative tests with 32 different original images and 5 different existing detectors. Results demonstrate the superior performance of each new measure within IV-INDPM in reaching a much closer agreement with human subjective evaluation, compared to existing measures in INDPM. Even though five new measures are efficient in evaluating detectors’ performance from different perspectives, a new benchmark algorithm (IND-BA) is proposed as a robust and overall metric for ease of general-purpose use by making the most of these five new measures. Comparison results demonstrate its efficiency and accuracy.