Back to articles
Articles
Volume: 29 | Article ID: art00012
Image
On the Perceptual Factors Underlying the Quality of PostCompression Enhancement of Textures
  DOI :  10.2352/ISSN.2470-1173.2017.14.HVEI-123  Published OnlineJanuary 2017
Abstract

The addition of white noise to an image has been shown to increase the perceived sharpness of the image's blurred regions under certain conditions. Additive white noise has also been shown to increase the visual quality a compressed image, a finding which has been attributed, in large part, to the noise's ability to simulate textures that have been lost via the compression. To explore the perceptual underpinnings of this enhancing effect, in this paper, we tested whether the noise can be tuned based on properties of the source texture to provide even greater improvements in quality as compared to white noise. We used a parametric texture-synthesis algorithm to generate statistically and spectrally shaped noise patterns, which were scaled in contrast and then added to corresponding compressed texture regions. Subjects reported both the optimal contrast scaling factors and the associated quality improvement scores relative to the distorted regions. Our results indicate that the addition of the shaped noise can provide markedly greater quality improvements compared to white noise, a finding which cannot be explained by the mere presence of high-frequency content. We discuss how the optimal contrast scalings might be predicted, and we examine the performances of existing quality assessment algorithms on our enhanced images.

Subject Areas :
Views 30
Downloads 1
 articleview.views 30
 articleview.downloads 1
  Cite this article 

Yusizwan M. Yaacob, Yi Zhang, Damon M. Chandler, "On the Perceptual Factors Underlying the Quality of PostCompression Enhancement of Texturesin Proc. IS&T Int’l. Symp. on Electronic Imaging: Human Vision and Electronic Imaging,  2017,  pp 97 - 103,  https://doi.org/10.2352/ISSN.2470-1173.2017.14.HVEI-123

 Copy citation
  Copyright statement 
Copyright © Society for Imaging Science and Technology 2017
72010604
Electronic Imaging
2470-1173
Society for Imaging Science and Technology