Blind Image Quality Assessment Based on Multichannel Feature Fusion and Label Transfer

• Published in: IEEE transactions on circuits and systems for video technology Vol. 26; no. 3; pp. 425 - 440
• Main Authors: Qingbo Wu, Hongliang Li, Fanman Meng, Ngan, King N., Luo, Bing, Huang, Chao, Zeng, Bing
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.03.2016; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Assessments; BIQA; Blinds; Channels; Discrete cosine transform; Discrete cosine transforms; Domains; Entropy; Feature extraction; Image color analysis; Image management; Image quality; Image retrieval; Label Transfer; Labels; Mathematical models; Multi-channel features fusion; Performance evaluation; Prediction models; Quality; Quality assessment; Visualization; Wavelet analysis; Wavelet domain; label transfer (LT); multichannel features fusion; Blind image quality assessment (BIQA)

In this paper, we propose an efficient blind image quality assessment (BIQA) algorithm, which is characterized by a new feature fusion scheme and a k-nearest-neighbor (KNN)-based quality prediction model. Our goal is to predict the perceptual quality of an image without any prior information of its...