Variable window width kernel estimates of probability densities

1988 ◽  
Vol 80 (1) ◽  
pp. 37-49 ◽  
Author(s):  
Peter Hall ◽  
J. S. Marron
Keyword(s):  
Kernel Estimates ◽  
Window Width ◽  
Probability Densities ◽  
Variable Window

scholarly journals Variable window width kernel estimates of probability densities

1992 ◽  
Vol 91 (1) ◽  
pp. 133-133
Author(s):  
Peter Hall ◽  
J. S. Marron
Keyword(s):  
Kernel Estimates ◽  
Window Width ◽  
Probability Densities ◽  
Variable Window

scholarly journals Improved Variable Window Kernel Estimates of Probability Densities

1995 ◽  
Vol 23 (1) ◽  
pp. 1-10 ◽  
Author(s):  
Peter Hall ◽  
Tien Chung Hu ◽  
J. S. Marron
Keyword(s):  
Kernel Estimates ◽  
Probability Densities ◽  
Variable Window

Acute Stroke: Improved Nonenhanced CT Detection—Benefits of Soft-Copy Interpretation by Using Variable Window Width and Center Level Settings

Radiology ◽  
1999 ◽  
Vol 213 (1) ◽  
pp. 150-155 ◽  
Author(s):  
Michael H. Lev ◽  
Jeffrey Farkas ◽  
Joseph J. Gemmete ◽  
Syeda T. Hossain ◽  
George J. Hunter ◽  
...  
Keyword(s):  
Acute Stroke ◽  
Window Width ◽  
Soft Copy ◽  
Variable Window

Image Focus Measure Based on Energy of High Frequency Components in S-Transform

2013 ◽  
pp. 162-180
Author(s):  
Muhammad Tariq Mahmood ◽  
Tae-Sun Choi
Keyword(s):  
High Frequency ◽  
Window Size ◽  
Accurate Method ◽  
Image Sharpness ◽  
Focus Measure ◽  
Window Width ◽  
S Transform ◽  
Variable Window ◽  
Focus Image ◽  
Frequency Components

Focus measure computes sharpness or high frequency contents in an image. It plays an important role in many image processing and computer vision applications such as shape from focus (SFF) techniques and multi-focus image fusion algorithms. In this chapter, we discuss different focus measures in spatial as well as in the transform domains. In addition, we suggest a novel focus measure in S-transform domain, which is based on the energy of high frequency components. A localized spectrum, by using variable window size, provides a more accurate method of measuring image sharpness as compared to other focus measures proposed in spectral domains. An optimal focus measure is obtained by selecting an appropriate frequency dependent window width. The performance of the proposed focus measure is compared with those of existing focus measures in terms of three dimensional shape recovery and all-in-focus image generation. Experimental results demonstrate the effectiveness of the proposed focus measure.

Image Focus Measure Based on Energy of High Frequency Components in S-Transform

2011 ◽  
pp. 189-208
Author(s):  
Muhammad Tariq Mahmood ◽  
Tae-Sun Choi
Keyword(s):  
High Frequency ◽  
Window Size ◽  
Accurate Method ◽  
Image Sharpness ◽  
Focus Measure ◽  
Window Width ◽  
S Transform ◽  
Variable Window ◽  
Focus Image ◽  
Frequency Components

Focus measure computes sharpness or high frequency contents in an image. It plays an important role in many image processing and computer vision applications such as shape from focus (SFF) techniques and multi-focus image fusion algorithms. In this chapter, we discuss different focus measures in spatial as well as in the transform domains. In addition, we suggest a novel focus measure in S-transform domain, which is based on the energy of high frequency components. A localized spectrum, by using variable window size, provides a more accurate method of measuring image sharpness as compared to other focus measures proposed in spectral domains. An optimal focus measure is obtained by selecting an appropriate frequency dependent window width. The performance of the proposed focus measure is compared with those of existing focus measures in terms of three dimensional shape recovery and all-in-focus image generation. Experimental results demonstrate the effectiveness of the proposed focus measure.

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