A color intensity invariant low-level feature optimization framework for image quality assessment

作者：Kottayil Navaneeth K; Cheng Irene^*; Dufaux Frederic; Basu Anup

来源：Signal, Image and Video Processing, 2016, 10(6): 1169-1176.

DOI：10.1007/s11760-016-0873-x

• Low-level feature extraction
• Perceptual quality
• Color adaptation
• Image quality assessment (IQA)
• Center-surround frequency scaling
• Two-tier normalization

Image quality assessment (IQA) algorithms evaluate the perceptual quality of an image using evaluation scores that assess the similarity or difference between two images. We propose a new low-level feature-based IQA technique, which applies filter-bank decomposition and center-surround methodology. Differing from existing methods, our model incorporates color intensity adaptation and frequency scaling optimization at each filter-bank level and spatial orientation to extract and enhance perceptually significant features. Our computational model exploits the concept of object detection and encapsulates characteristics proposed in other IQA algorithms in a unified architecture. We also propose a systematic approach to review the evolution of IQA algorithms using unbiased test datasets, instead of looking at individual scores in isolation. Experimental results demonstrate the feasibility of our approach.

• 出版日期2016-9
• 单位TELECOM ParisTech