This project is an attempt to explore a human element not easily solved in the image processing communities. The problem statement is vague but important to address. What is a good image? More specifically, if a low contrast image is presented, at what level of enhancement is good enough for a human observer?
Help me by completing
the image comparison test! »
ISCAS 2012
Data [1]
Journal Code 2012
Under review
Color Ellipsoid Framework
Paper Under Review [7]
This work presents a new contrast enhancement metric (CEM) that is trained using several simple contrast measures and mean opinion scores obtained from human observations. Our goal is to train the algorithm to mimic a human when selecting an image with the best contrast between two images. For example, the algorithm will accept two images of the same scene with differing (unknown) contrast and will choose which of the two images is `better' according to what a human believes is `better'. See Figure 1 for an example of how to use the CEM.
Given an input image, the CEM will measure the performance of each contrast enhancement filter from the filter suite. The filter with the highest CEM value will be chose for that input image.
This image sent was sorted using the CEM by comparing to each image pair. From left to right is increase in perceptual contrast.
The following figures and tables are supplemental materials for the journal A No-Reference Perceptual Based Contrast Enhancement Metric for Ocean Scenes in Fog.
Online Test Example and Demographics. The gender, age, education, expertise and enhancement usage statistics were captured for each observer and illustrated in each plot.
These are the original images used for the subjective tests along with 7 different enhanced versions.
Each original image---which had fog or haze---was manipulated with 7 different methods in this table.
The average error and standard deviation for each sub-metric.
For the sake of space and clarity, we only show the results from the CEMhc and CEMh methods because they produced the highest averaged correlations. Each row is a correlation measurement for each scene. The last row is the average over all the scenes.