A No-Reference Objective Image Sharpness Metric Based on the Notion of Just Noticeable Blur (JNB)

• Published in: IEEE transactions on image processing Vol. 18; no. 4; pp. 717 - 728
• Main Authors: Ferzli, R., Karam, L.J.
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01.04.2009; Institute of Electrical and Electronics Engineers; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Accuracy; Applied sciences; Correlation; Detection, estimation, filtering, equalization, prediction; Displays; Exact sciences and technology; HVS; Image analysis; image assessment; Image coding; Image processing; Image quality; Image restoration; Information, signal and communications theory; Mathematical models; no-reference; objective; perception; Printing; Quantization; Sharpness; sharpness metric; Signal and communications theory; Signal processing; Signal, noise; Telecommunications and information theory; Testing; Video compression; Performance evaluation; Image resolution; HVS; image assessment; High precision; Blurred image; objective; perception; Image quality; Metric; sharpness metric; no-reference; Image sharpness
• ISSN: 1057-7149; 1941-0042
• DOI: 10.1109/TIP.2008.2011760

This work presents a perceptual-based no-reference objective image sharpness/blurriness metric by integrating the concept of just noticeable blur into a probability summation model. Unlike existing objective no-reference image sharpness/blurriness metrics, the proposed metric is able to predict the relative amount of blurriness in images with different content. Results are provided to illustrate the performance of the proposed perceptual-based sharpness metric. These results show that the proposed sharpness metric correlates well with the perceived sharpness being able to predict with high accuracy the relative amount of blurriness in images with different content.