A Statistical Evaluation of Recent Full Reference Image Quality Assessment Algorithms

• Published in: IEEE transactions on image processing Vol. 15; no. 11; pp. 3440 - 3451
• Main Authors: Sheikh, H.R., Sabir, M.F., Bovik, A.C.
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01.11.2006; Institute of Electrical and Electronics Engineers; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithm design and analysis; Algorithms; Applied sciences; Assessments; Data Interpretation, Statistical; Detection, estimation, filtering, equalization, prediction; Distortion; Exact sciences and technology; Human; Humans; Image Enhancement - methods; Image Interpretation, Computer-Assisted - methods; Image processing; Image quality; Image quality assessment performance; image quality study; Information Storage and Retrieval - methods; Information, signal and communications theory; Judgments; Laboratories; Performance analysis; Performance evaluation; PSNR; Quality assessment; Quality Control; Signal and communications theory; Signal processing; Signal, noise; Software; Software Validation; Studies; subjective quality assessment; Telecommunications and information theory; Testing; Video compression; Performance evaluation; Image processing; Algorithm; Image quality assessment performance; Subjective evaluation; Video signal processing; Image quality; subjective quality assessment; image quality study; Algorithm performance; Quality control; Signal distortion; Image evaluation
• ISSN: 1057-7149; 1941-0042
• DOI: 10.1109/TIP.2006.881959

Measurement of visual quality is of fundamental importance for numerous image and video processing applications, where the goal of quality assessment (QA) algorithms is to automatically assess the quality of images or videos in agreement with human quality judgments. Over the years, many researchers...