Abstract. Sharpening filters increase the depth of digital images by adding a fraction of their gradient. This portion is tuned by a coefficient which is usually selected according to rules of thumb or subjective evaluation. This paper proposes statistical measures for designing such parameter in a nearly automatic way, avoiding subjective evaluations. The proposed measures are based on the distance between sharpened and equalized images, which serve as an early reference, and test statistics of uniformity of the luminance histogram. More complex measures, based on the trade-off between skewness and kurtosis, and variance and autocovariance of the sharpened image, are also studied. Numerical applications to various kinds of digital images s...
AbstractOne of the most challenging problems for researchers in the field of image processing is ima...
We address the problem of image quality assessment for natural images, focusing on No Reference (NR)...
We address the problem of image quality assessment for natural images, focusing on No Reference (NR)...
Sharpening filters increase the depth of digital images by adding a fraction of their gradient. This...
Recently, problems of digital image sharpness determination are becoming more relevant and significa...
Aimed to find the additive magnitude automatically and adaptively, we propose a three-step and mode...
License, which permits unrestricted use, distribution, and reproduction in any medium, provided the ...
Sharpening is a powerful image transformation because sharp edges can bring out image details. Sharp...
In this paper an evaluation of the degree of change in the perceived image sharpness with changes in...
International audienceImage sharpening is a post-processing technique employed for the artificial en...
We present three research topics related to digital photography:image sharpness, image interpolation...
We propose an automatic method for image sharpening that maximizes the perceptual sharpness while pr...
We recently proposed a region-based measure of image edge profile acutance to characterize the sharp...
Abstract—In this paper, a no-reference perceptual sharpness metric based on a statistical analysis o...
Abstract—This paper presents an algorithmdesigned tomeasure the local perceived sharpness in an imag...
AbstractOne of the most challenging problems for researchers in the field of image processing is ima...
We address the problem of image quality assessment for natural images, focusing on No Reference (NR)...
We address the problem of image quality assessment for natural images, focusing on No Reference (NR)...
Sharpening filters increase the depth of digital images by adding a fraction of their gradient. This...
Recently, problems of digital image sharpness determination are becoming more relevant and significa...
Aimed to find the additive magnitude automatically and adaptively, we propose a three-step and mode...
License, which permits unrestricted use, distribution, and reproduction in any medium, provided the ...
Sharpening is a powerful image transformation because sharp edges can bring out image details. Sharp...
In this paper an evaluation of the degree of change in the perceived image sharpness with changes in...
International audienceImage sharpening is a post-processing technique employed for the artificial en...
We present three research topics related to digital photography:image sharpness, image interpolation...
We propose an automatic method for image sharpening that maximizes the perceptual sharpness while pr...
We recently proposed a region-based measure of image edge profile acutance to characterize the sharp...
Abstract—In this paper, a no-reference perceptual sharpness metric based on a statistical analysis o...
Abstract—This paper presents an algorithmdesigned tomeasure the local perceived sharpness in an imag...
AbstractOne of the most challenging problems for researchers in the field of image processing is ima...
We address the problem of image quality assessment for natural images, focusing on No Reference (NR)...
We address the problem of image quality assessment for natural images, focusing on No Reference (NR)...