A Simple Relationship Between SSIM and PSNR for DCT-Based Compressed Images and Video: SSIM as Content-Aware PSNR
Maria G. Martini
Abstract
The aim of this paper is to show how the structural similarity metric SSIM for image quality assessment can be seen in many cases, such as DCT-based compressed images and video, as a content-aware version of the peak signal-to-noise ratio (PSNR). In fact, under some assumptions described in the paper, the first can be derived directly from the latter based on a single content-dependent parameter, i.e. the variance of the image / video frame, not requiring joint access to original and compressed image/frames. Results show the validity of the assumptions and high accuracy for the derivation / estimation, in particular at quality levels of interest in real use cases.
Topics & Concepts
Discrete cosine transformComputer scienceArtificial intelligencePeak signal-to-noise ratioMetric (unit)Computer visionFrame (networking)Similarity (geometry)Variance (accounting)Image qualityVideo qualityImage (mathematics)Simple (philosophy)Joint (building)Pattern recognition (psychology)Content (measure theory)MathematicsMathematical analysisAccountingTelecommunicationsPhilosophyOperations managementBusinessArchitectural engineeringEconomicsEngineeringEpistemologyImage and Video Quality AssessmentImage and Signal Denoising MethodsAdvanced Image Processing Techniques