| Title |
No-reference Image Contrast Quality Assessment based on the Degree of Uniformity in Probability Distribution |
| Authors |
(Wonvin Kim) ; (Changhoon Yim) |
| DOI |
https://doi.org/10.5573/IEIESPC.2022.11.2.85 |
| Keywords |
Contrast; Entropy; Image quality assessment; Image dehazing |
| Abstract |
We propose a novel contrast-based no-reference image quality assessment (NR-IQA) method. The proposed method quantifies the degree of uniformity in the probability distribution of the pixel values of an image to measure contrast quality without the need for a reference image. To quantify the degree of symmetric uniformity in the distribution of pixel values for image contrast assessment, we divide the intensity levels into left and right ranges recursively at each depth as a binary tree. This symmetric hierarchical recursive calculation of the degree of uniformity for contrast measurement provides a good metric for NR-IQA. Experimental results show that the proposed method is more consistent with the levels of contrast decrement and is superior in assessing contrast-enhanced and dehazed images compared with state-of-the-art and classic NR-IQA methods. The proposed method is more suited to real-time applications due to its lower computational complexity compared with previous methods. |