Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2011 · 23 citations · 0 references
ComputingComputer ScienceComputer VisionQuality ImprovementVisual PerceptionImage AnalysisImage QualityImage Quality AssessmentImage Quality AssuranceQuality MetricsImage Performance MetricsImage Quality MetricsImage Similarity MeasurementPerceptual Quality AssessmentQuality AssessmentSimilarity MeasuresSimilarity MetricsSubjective Image Quality Assessment
Image similarity measures are crucial for image processing applications which require comparisons to ideal reference images in order to assess performance. The Structural Similarity (SSIM), Gradient Structural Similarity (GSSIM), 4-component SSIM (4-SSIM) and 4-component GSSIM (4-GSSIM) indexes are motivated by the fact that the human visual system is adapted to extract local structural information. In this paper, we propose a new measure which enhances the gradient information used for quality assessment. An analysis of the proposed image similarity measure using the LIVE database of distorted images and their corresponding subjective evaluations of visual quality illustrate the improved performance of the proposed metric.