Content-weighted mean-squared error for quality assessment of compressed images

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journal

10 Scopus Citations
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Author(s)

  • Ke Gu
  • Guangtao Zhai
  • Siwei Ma
  • Xiaokang Yang
  • Wenjun Zhang

Detail(s)

Original languageEnglish
Pages (from-to)803-810
Journal / PublicationSignal, Image and Video Processing
Volume10
Issue number5
Online published23 Sep 2015
Publication statusPublished - Jul 2016
Externally publishedYes

Abstract

Image quality assessment (IQA) has been intensively studied, especially for the full-reference (FR) scenario. However, only the mean-squared error (MSE) is widely employed in compression. Why other IQA metrics work ineffectively? We first sum up three main limitations including the computational time, portability, and working manner. To address these problems, we then in this paper propose a new content-weighted MSE (CW-MSE) method to assess the quality of compressed images. The design principle of our model is to use adaptive Gaussian convolution to estimate the influence of image content in a block-based manner, thereby to approximate the human visual perception to image quality. Results of experiments on six popular subjective image quality databases (including LIVE, TID2008, CSIQ, IVC, Toyama and TID2013) confirm the superiority of our CW-MSE over state-of-the-art FR IQA approaches.

Research Area(s)

  • Image compression, Image content, Image quality assessment (IQA), Mean-squared error (MSE)

Citation Format(s)

Content-weighted mean-squared error for quality assessment of compressed images. / Gu, Ke; Wang, Shiqi; Zhai, Guangtao; Ma, Siwei; Yang, Xiaokang; Zhang, Wenjun.

In: Signal, Image and Video Processing, Vol. 10, No. 5, 07.2016, p. 803-810.

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journal