IEEE Signal Processing Letters · 2014 · 109 citations · 20 references
ArtsRadiologyComputer VisionDigital ImagingQuality EngineeringData CompressionImage CompressionImage QualityImage Quality AssessmentLossy Data CompressionQuality MetricsCompressionImage Quality BenchmarkingImage Quality MetricsNo-reference Image Quality AssessmentNo-reference Quality AssessmentRelevance Estimation
This letter presents a no-reference quality assessment algorithm for JPEG compressed images (NJQA). Our method does not specifically aim to measure blockiness. Instead, quality is estimated by first counting the number of zero-valued DCT coefficients within each block, and then using a map, which we call the quality relevance map, to weight these counts. The quality relevance map for an image is a map that indicates which blocks are naturally uniform (or near-uniform) vs. which blocks have been made uniform (or near-uniform) via JPEG compression. Testing on various image-quality databases demonstrates that NJQA is either competitive with or outperforms modern competing methods on JPEG images.
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Image quality assessment: from error visibility to structural similarity
Zhou Wang, Alan C. Bovik, Hamid R. Sheikh et al. · IEEE Transactions on Image Processing · 2004 · 56K citations