A new image quality measure for assessment of histogram equalization-based contrast enhancement techniques

• Main Author: Chen S.-D.
• Other Authors: 7410253413
• Format: Article
• Published: Elsevier Inc. 2023
• Subjects: Contrast enhancement; Distortions; Histogram equalization; Quality measures; Visual perception; Correlation methods; Distortion (waves); Entropy; Equalizers; Graphic methods; Image enhancement; Mean square error; Quality control; Vision; Contrast Enhancement; Histogram equalizations; Information fidelity criterion; Pearson correlation coefficients; Root mean square errors; Subjective quality assessments; Image quality

Absolute Mean Brightness Error (AMBE) and Entropy are among the two most popular IQMs used to assess Histogram Equalization (HE) based techniques. To the best of author's knowledge, there is no evaluation report on how well the two IQMs correlate to human opinion. This paper reviews and discusses the potential flaws in using AMBE and Entropy to assess HE-based techniques. This paper presents results of a subjective quality assessment in which image quality data obtained from 1935 human observer opinion scores were used to evaluate the IQMs. The statistical evaluation results show that the two IQMs have poor correlation with human mean opinion score (MOS); Pearson Correlation Coefficient (PCC)<0.4, Root Mean Square Error (RMSE)>0.75, Outlier Ratio (OR)>20%. A new IQM which takes into account important properties of human visual perception (HVP) is proposed. It is tested and found to have significantly better correlation (PCC>0.86, RMSE<0.39 and OR=0%). The proposed IQM also outperforms Multi-Scale Structural Similarity (MSSIM) and Information Fidelity Criterion-based (IFC) measure, which are two prominent fidelity-based IQMs. � 2012 Elsevier Inc. All rights reserved.