${\bf S}_{3}$: A Spectral and Spatial Measure of Local Perceived Sharpness in Natural Images

By Cuong T. Vu, Thien D. Phan, Damon M. Chandler. IEEE Transactions on Image Processing, 2012

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How researchers see this paper

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Blind Quality Assessment Based on Pseudo-Reference Image (2018, background): “A spectral and spatial sharpness (S3) was proposed in [24].”
Learning a No-Reference Quality Assessment Model of Enhanced Images With Big Data (2018, background): “Actually, these years have seen quite a few works dedicated to sharpness assessment [50, 51, 52].”
Sharpness-Aware Low-Dose CT Denoising Using Conditional Generative Adversarial Network (2017, background): “gradient [55], local binary pattern [69], power spectrum slope [55, 62], discrete cosine transform (DCT) coefficient [21].”
No-Reference Image Sharpness Assessment in Autoregressive Parameter Space (2015, methodology): “Comparison of local sharpness maps of ground truth, S3, FISHbb and NFEQM using representative images in [17].”