Non-shift edge based ratio (NSER): An image quality assessment metric based on early vision features

Min Zhang, Xuanqin Mou, Lei Zhang

Research output: Journal article publicationJournal articleAcademic researchpeer-review

43 Citations (Scopus)

Abstract

How to evaluate the image perceptual quality is a fundamental problem in image and video processing, and various methods have been proposed for image quality assessment (IQA). This letter presents a novel IQA metric, which is based on the image primitive features produced in the earliest processing stage of human visual system. The procedures involved in the proposed method include computing the response of classical receptive fields, zero-crossing detection, and non-shift edge based ratio (NSER) calculation. The proposed IQA metric is very simple but very effective. The experimental results on benchmark databases show that the NSER index has very high consistency with the psychological evaluation, performing much better than most state-of-the-art IQA metrics.
Original languageEnglish
Article number5729787
Pages (from-to)315-318
Number of pages4
JournalIEEE Signal Processing Letters
Volume18
Issue number5
DOIs
Publication statusPublished - 6 Apr 2011

Keywords

  • Image quality assessment (IQA)
  • non-shift edge (NSE)
  • non-shift edge based ratio (NSER)
  • zero-crossing

ASJC Scopus subject areas

  • Signal Processing
  • Applied Mathematics
  • Electrical and Electronic Engineering

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