A histogram modification framework and its application for image contrast enhancement
IEEE Transactions on Image Processing
Contrast enhancement using brightness preserving bi-histogram equalization
IEEE Transactions on Consumer Electronics
Image enhancement based on equal area dualistic sub-image histogram equalization method
IEEE Transactions on Consumer Electronics
IEEE Transactions on Consumer Electronics
Brightness preserving histogram equalization with maximum entropy: a variational perspective
IEEE Transactions on Consumer Electronics
A Dynamic Histogram Equalization for Image Contrast Enhancement
IEEE Transactions on Consumer Electronics
Fast Image/Video Contrast Enhancement Based on Weighted Thresholded Histogram Equalization
IEEE Transactions on Consumer Electronics
Multi-Histogram Equalization Methods for Contrast Enhancement and Brightness Preserving
IEEE Transactions on Consumer Electronics
Brightness Preserving Dynamic Histogram Equalization for Image Contrast Enhancement
IEEE Transactions on Consumer Electronics
IEEE Transactions on Consumer Electronics
Image sharpening using sub-regions histogram equalization
IEEE Transactions on Consumer Electronics
Bi-histogram equalization with a plateau limit for digital image enhancement
IEEE Transactions on Consumer Electronics
Brightness preserving dynamic fuzzy histogram equalization
IEEE Transactions on Consumer Electronics
Adaptive contrast enhancement methods with brightness preserving
IEEE Transactions on Consumer Electronics
Quadrants dynamic histogram equalization for contrast enhancement
IEEE Transactions on Consumer Electronics
Image contrast enhancement using bi-histogram equalization with neighborhood metrics
IEEE Transactions on Consumer Electronics
Image enhancement using a fusion framework of histogram equalization and laplacian pyramid
IEEE Transactions on Consumer Electronics
Image quality assessment: from error visibility to structural similarity
IEEE Transactions on Image Processing
An information fidelity criterion for image quality assessment using natural scene statistics
IEEE Transactions on Image Processing
A Statistical Evaluation of Recent Full Reference Image Quality Assessment Algorithms
IEEE Transactions on Image Processing
Image enhancement using Exposure based Sub Image Histogram Equalization
Pattern Recognition Letters
| Hi-index | 0.00 |
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)0.75, 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 (PCC0.86, RMSE