Image Quality Assessment Based on Perceptual Structural Similarity

We present a full reference objective image quality assessment technique which is based on the properties of the human visual system (HVS). It consists of two major components: 1) structural similarity measurement (SSIM) between the reference and distorted images, mimicking the overall functionality of HVS in a top down frame work. 2) A visual attention model which indicates perceptually important regions in the reference image based on the characteristics of intermediate and higher visual processes through the use of Importance Maps. Structural similarity in a region is weighted, depending on the perceptual importance of the region to arrive at Perceptual Structural Similarity Metric (PSSIM) indicative of the image quality.

[1]  J. Findlay The Visual Stimulus for Saccadic Eye Movements in Human Observers , 1980, Perception.

[2]  Alan C. Bovik,et al.  Image quality assessment using natural scene statistics , 2004 .

[3]  Y Y Zeevi,et al.  Visual assessment of variable-resolution imagery. , 1995, Journal of the Optical Society of America. A, Optics, image science, and vision.

[4]  L. Kaufman,et al.  “Center-of-gravity” Tendencies for fixations and flow patterns , 1969 .

[5]  John A. Saghri,et al.  Image Quality Measure Based On A Human Visual System Model , 1989 .

[6]  D. S. Wooding,et al.  The relationship between the locations of spatial features and those of fixations made during visual examination of briefly presented images. , 1996, Spatial vision.

[7]  K. Cave The FeatureGate model of visual selection , 1999, Psychological research.

[8]  A. L. Yarbus,et al.  Eye Movements and Vision , 1967, Springer US.

[9]  Eero P. Simoncelli,et al.  Image quality assessment: from error visibility to structural similarity , 2004, IEEE Transactions on Image Processing.

[10]  Alan C. Bovik,et al.  41 OBJECTIVE VIDEO QUALITY ASSESSMENT , 2003 .

[11]  A. Bovik,et al.  OBJECTIVE VIDEO QUALITY ASSESSMENT , 2003 .

[12]  Nick G. Kingsbury,et al.  A distortion measure for blocking artifacts in images based on human visual sensitivity , 1995, IEEE Trans. Image Process..

[13]  Zhou Wang,et al.  Image Quality Assessment: From Error Measurement to Structural Similarity , 2004 .

[14]  Wilson S. Geisler,et al.  Implementation of a foveated image coding system for image bandwidth reduction , 1996, Electronic Imaging.

[15]  Norman B. Nill,et al.  A Visual Model Weighted Cosine Transform for Image Compression and Quality Assessment , 1985, IEEE Trans. Commun..

[16]  Jeffrey Lubin,et al.  A VISUAL DISCRIMINATION MODEL FOR IMAGING SYSTEM DESIGN AND EVALUATION , 1995 .

[17]  Rafael C. González,et al.  Local Determination of a Moving Contrast Edge , 1985, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[18]  John W. Senders,et al.  Distribution of visual attention in static and dynamic displays , 1997, Electronic Imaging.

[19]  John F. Canny,et al.  A Computational Approach to Edge Detection , 1986, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[20]  Andrew B. Watson,et al.  DCT quantization matrices visually optimized for individual images , 1993, Electronic Imaging.

[21]  Bernd Girod,et al.  What's wrong with mean-squared error? , 1993 .

[22]  Paul S. Fisher,et al.  Image quality measures and their performance , 1995, IEEE Trans. Commun..

[23]  Scott J. Daly,et al.  Visible differences predictor: an algorithm for the assessment of image fidelity , 1992, Electronic Imaging.

[24]  Wa James Tam,et al.  Static and dynamic spatial resolution in image coding: an investigation of eye movements , 1991, Electronic Imaging.

[25]  Jean-Bernard Martens,et al.  Quality asessment of coded images using numerical category scaling , 1995, Other Conferences.

[26]  Zhou Wang,et al.  Video quality assessment based on structural distortion measurement , 2004, Signal Process. Image Commun..

[27]  Stefan Winkler,et al.  Video Quality Experts Group: current results and future directions , 2000, Visual Communications and Image Processing.

[28]  Andrew B. Watson,et al.  Digital images and human vision , 1993 .