Improving Performance of IQA Algorithm: A Simplified Approach to SSIM based on Image Gradients

Objectives: To propose a fast and efficient algorithm for Full Reference Image Quality Assessment (FR-IQA) that can evaluate the quality of a distorted image accurately. Methods/Statistical Analysis: The proposed approach uses SSIM (Structural Similarity Index for Measuring Image) algorithm based on image gradients. SSIM algorithm has been widely accepted as an effective tool for estimating image quality. The quality estimation capability of SSIM has been enhanced by using image gradients. In this paper, the SSIM based on image gradients has been simplified and optimized to reduce the computational complexity, thereby to improve the execution speed and to improve the quality estimation capability. Findings: The proposed algorithm is computationally simple compared to SSIM and Gradient based SSIM. There has been significant improvement in the execution speed and quality prediction capability of the proposed algorithm compared to SSIM and Gradient based SSIM for various types of distortions. This simplified version of SSIM based on gradients has been extensively tested on popular image databases. The results confirm its effectiveness, efficiency and consistency in estimating the image quality. Applications/Improvements: The proposed algorithm is suitable in IQA applications where improved prediction accuracy and execution speed are important.