Name
Abstract | ||
|---|---|---|
An effective contrast enhancement method should not only improve the perceptual quality of an image but should also avoid adding any artifacts or affecting naturalness of images. This makes Contrast Enhancement Evaluation (CEE) a challenging task in the sense that both the improvement in image quality and unwanted side-effects need to be checked for. Currently, there is no single CEE metric that works well for all kinds of enhancement criteria. In this paper, we propose a new Multi-Criteria CEE (MCCEE) measure which combines different metrics effectively to give a single quality score. In order to fully exploit the potential of these metrics, we have further proposed to apply them on the decomposed image using wavelet transform. This new metric has been tested on two natural image contrast enhancement databases as well as on medical Computed Tomography (CT) images. The results show a substantial improvement as compared to the existing evaluation metrics. The code for the metric is available at: https://github.com/zakopz/MCCEE-Contrast-Enhancement-Metric. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1109/MMSP48831.2020.9287051 | 2020 IEEE 22nd International Workshop on Multimedia Signal Processing (MMSP) |
Keywords | DocType | ISSN |
Contrast Enhancement Evaluation,image quality,Contrast enhancement,wavelet transform,medical image quality | Conference | 2163-3517 |
ISBN | Citations | PageRank |
978-1-7281-9323-6 | 0 | 0.34 |
References | Authors | |
13 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zohaib Amjad Khan | 1 | 0 | 0.34 |
| Azeddine Beghdadi | 2 | 562 | 83.96 |
| Faouzi Alaya Cheikh | 3 | 168 | 38.47 |
| Mounir Kaaniche | 4 | 74 | 13.41 |
| Muhammad Ali Qureshi | 5 | 0 | 1.35 |