A survey of hybrid MC/DPCM/DCT video coding distortions
Signal Processing - Special issue on image and video quality metrics
Issues in vision modeling for perceptual video quality assessment
Signal Processing
No-reference JPEG-image quality assessment using GAP-RBF
Signal Processing
A distortion measure for blocking artifacts in images based on human visual sensitivity
IEEE Transactions on Image Processing
A perceptually tuned subband image coder based on the measure of just-noticeable-distortion profile
IEEE Transactions on Circuits and Systems for Video Technology
Efficient DCT-domain blind measurement and reduction of blocking artifacts
IEEE Transactions on Circuits and Systems for Video Technology
Motion-compensated residue preprocessing in video coding based on just-noticeable-distortion profile
IEEE Transactions on Circuits and Systems for Video Technology
A perceptually relevant approach to ringing region detection
IEEE Transactions on Image Processing
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A novel no-reference blockiness metric that provides a quantitative measure of blocking annoyance in block-based DCT coding is presented. The metric incorporates properties of the human visual system (HVS) to improve its reliability, while the additional cost introduced by the HVS is minimized to ensure its use for real-time processing. This is mainly achieved by calculating the local pixel-based distortion of the artifact itself, combined with its local visibility by means of a simplified model of visual masking. The overall computation efficiency and metric accuracy is further improved by including a grid detector to identify the exact location of blocking artifacts in a given image. The metric calculated only at the detected blocking artifacts is averaged over all blocking artifacts in the image to yield an overall blockiness score. The performance of this metric is compared to existing alternatives in literature and shows to be highly consistent with subjective data at a reduced computational load. As such, the proposed blockiness metric is promising in terms of both computational efficiency and practical reliability for real-life applications.