Natural DCT statistics approach to no-reference image quality assessment

General-purpose no-reference image quality assessment approaches still lag the advances in full-reference methods. Most no-reference methods are either distortion specific (i.e. they quantify one or more distortions such as blur, blockiness, or ringing), or they train a learning machine based on a large number of features. In this approach, we propose a discrete cosine transform (DCT) statistics-based support vector machine (SVM) approach based on only 3 features in the DCT domain. The approach extracts a very small number of features and is entirely in the DCT domain, making it computationally convenient. The results are shown to correlate highly with human visual perception of quality.

• Type: Journal
• Year: 2010
• Where: ICIP
• Authors: Michele A. Saad, Alan C. Bovik, Christophe Charrier
• Keywords: DCT Domain, General-purpose No-reference Image, ICIP 2010, Image Processing, Most No-reference Methods