An accelerated general purpose no-reference image quality assessment metric and an image fusion technique

Date of Award


Degree Name

M.S. in Electrical Engineering


Department of Electrical and Computer Engineering


Advisor: Eric John Balster


This study suggests improvements and an extension for the No-Reference Image Enhancement Quality Metric And Fusion (NRIE-QMF) Technique, that measures a perceptual quality score. To measure the quality score, the NRIE-QMF metric uses the image statistics based on brightness, contrast, and noise content. The NRIE-QMF uses several image inputs from various image enhancement methods (GHE, CLAHE, and LTSN) and calculates a score value for each pixels based on the local neighborhood statistics. Then respective pixel scores of each enhanced image are weighted and fused into one to create a combined image. The NRIE-QMF metric is analyzed for execution time using the MATLAB profiler. Few modification and optimization steps are carried out to increase the execution speed while maintaining a good output. Secondly, enhanced images are scored using the proposed metric and the score matrices are thresholded compared to the original image's score matrix to avoid over-amplification caused by some enhancement methods. Finally, it is shown that the proposed metric achieves a 85.8% speed increase compared to the NRIE-QMF method and generates a combined output image with a superior visual quality. Also, quality score of the new combined image results higher than those of the enhanced images used for fusion, demonstrating the superiority of the proposed method's fusion technique.


Imaging systems Image quality Evaluation, Image analysis, Threshold (Perception), Electrical Engineering, No-Reference Image Enhancement Quality Assessment, No-Reference Image Enhancement Quality Metric, NRIQA, NR-IQA, No-Reference Image Enhancement Quality Metric And Fusion Technique, visual quality

Rights Statement

Copyright 2016, author