Abstract
One of the most popular waveform based coding scheme for images is Transform coding. It is also known that the wavelet coefficients of no reference images possess certain regularities by the image distortions. The NRDPF-IQA (No Reference Distortion Patch Features-Image Quality Assessment) is one of the No-Reference Image Quality algorithms, which is the proposed algorithm in this paper. The proposed algorithm estimates quality based on features of the image. However the previous BRISQUE (Blind/Referenceless Image Spatial Quality Evaluator) algorithm operates based on low computational complexity and C-DIIVINE (complex extension of the DIIVINE) algorithm based on complex Gaussian scale mixture model. In this paper, we present NRDPF-IQA algorithm, which blindly assesses image quality based on advanced generalized Gaussian distortion model. All these distortions have characteristic features that are consistent across No-Reference images. We also compare the results with all existing algorithms. The experimental results show that this NRDPF-IQA to yield an improvement to perform the better results compare with other recent No-Reference algorithms.
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