An objective blurriness model is useful in various image processing applications. Especially,
a no-reference model is expected as a highly desirable approach due to its applicability to …

This paper presents an efficient no-reference metric that quantifies perceived image quality
induced by blur. Instead of explicitly simulating the human visual perception of blur, it …

In this Letter, we present a simple yet effective no-reference image blur assessment
algorithm based on local total variation. Firstly, we calculate a local image blurriness metric …

Measuring image blurriness is an important issue in image-quality assessment. The
blurriness affects the image quality by degrading the image's high frequency details in the …

The presence of blur artifact is an annoyance to image viewers, and affects the perceived
quality of the image. Telecommunication service providers and imaging product …

This paper presents a no-reference image blur metric that is based on the study of human
blur perception for varying contrast values. The metric utilizes a probabilistic model to …

Blur distortion appears in multimedia content due to acquisition, compression or
transmission errors. In this paper, a method is proposed to predict blur severity based on the …

Blur images are often subjected to the loss of high frequency content during acquisition,
compression and multimedia transmission. Hence, objective blur assessment is …

In this paper, we present an efficient no-reference image blur metric which is based on the
analysis of the spread of edge and the study of human blur perception for varying contrast …

Blur distortion is a common artifact in image communication and affects the perceived
sharpness of a digital image. In this paper, we capitalize on the mathematical knowledge of …