Implementation of a visual difference metric using commodity graphics hardware

Jered E. Windsheimer, Gary W. Meyer

Research output: Contribution to journalConference articlepeer-review

3 Scopus citations


A visual difference metric was implemented on a commodity graphics card to take advantage of the increased processing power available today in a Graphics Processing Unit (GPU). The specific algorithm employed was the Sarnoff Visual Discrimination Metric (Sarnoff VDM). To begin the implementation, the typical architecture of a contemporary GPU was analyzed and some general strategies were developed for performing image processing tasks on GPUs. The stages of the Sarnoff VDM were then mapped onto the hardware and the implementation was completed. A performance analysis showed that the algorithm's speed had been increased by an order of magnitude over the original version that only ran on a CPU. The same analysis showed that the energy stage was the most expensive in terms of both program size and processing time. An interactive version of the Sarnoff VDM was developed and some ideas for additional applications of GPU based visual difference metrics were suggested.

Original languageEnglish (US)
Pages (from-to)150-161
Number of pages12
JournalProceedings of SPIE - The International Society for Optical Engineering
StatePublished - 2004
EventHuman Vision and Electronic Imaging IX - San Jose, CA, United States
Duration: Jan 19 2004Jan 21 2004


  • Graphics Hardware
  • Graphics Processing Unit
  • Vision Model
  • Visual Difference Metric


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