Spatially Variant Smoothing Filter for Image Enhancement
Summary :
A new spatially variant smoothing filter is derived for image enhancement. The main object of this filter is to improve the output image of a linear spatially invariant image restoration filter such as Wiener filter. In this filter the processing for flat fields of image gray levels is quite different from that of edge portions of the image. As a new trial we apply one-dimensional smoothing to the edge portions. This is because it would be important that the edge line of an image is linked smoothly for our visual perception. For flat fields we divide these into three categories, 'full flat field', 'ordinary flat field', and 'less flat field'. In each field the unknown parameter of the new smoothing filter is determined optimally. The resulting smoothed image is more preferable for human eye.
- Publication
- IEICE TRANSACTIONS on transactions Vol.E68-E No.11 pp.757-762
- Publication Date
- 1985/11/25
- Publicized
- Online ISSN
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- Type of Manuscript
- PAPER
- Category
- Data Processing
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Hiroshi KONDO, Hiroyasu SAKAMOTO, "Spatially Variant Smoothing Filter for Image Enhancement" in IEICE TRANSACTIONS on transactions,
vol. E68-E, no. 11, pp. 757-762, November 1985, doi: .
Abstract: A new spatially variant smoothing filter is derived for image enhancement. The main object of this filter is to improve the output image of a linear spatially invariant image restoration filter such as Wiener filter. In this filter the processing for flat fields of image gray levels is quite different from that of edge portions of the image. As a new trial we apply one-dimensional smoothing to the edge portions. This is because it would be important that the edge line of an image is linked smoothly for our visual perception. For flat fields we divide these into three categories, 'full flat field', 'ordinary flat field', and 'less flat field'. In each field the unknown parameter of the new smoothing filter is determined optimally. The resulting smoothed image is more preferable for human eye.
URL: https://global.ieice.org/en_transactions/transactions/10.1587/e68-e_11_757/_p
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@ARTICLE{e68-e_11_757,
author={Hiroshi KONDO, Hiroyasu SAKAMOTO, },
journal={IEICE TRANSACTIONS on transactions},
title={Spatially Variant Smoothing Filter for Image Enhancement},
year={1985},
volume={E68-E},
number={11},
pages={757-762},
abstract={A new spatially variant smoothing filter is derived for image enhancement. The main object of this filter is to improve the output image of a linear spatially invariant image restoration filter such as Wiener filter. In this filter the processing for flat fields of image gray levels is quite different from that of edge portions of the image. As a new trial we apply one-dimensional smoothing to the edge portions. This is because it would be important that the edge line of an image is linked smoothly for our visual perception. For flat fields we divide these into three categories, 'full flat field', 'ordinary flat field', and 'less flat field'. In each field the unknown parameter of the new smoothing filter is determined optimally. The resulting smoothed image is more preferable for human eye.},
keywords={},
doi={},
ISSN={},
month={November},}
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TY - JOUR
TI - Spatially Variant Smoothing Filter for Image Enhancement
T2 - IEICE TRANSACTIONS on transactions
SP - 757
EP - 762
AU - Hiroshi KONDO
AU - Hiroyasu SAKAMOTO
PY - 1985
DO -
JO - IEICE TRANSACTIONS on transactions
SN -
VL - E68-E
IS - 11
JA - IEICE TRANSACTIONS on transactions
Y1 - November 1985
AB - A new spatially variant smoothing filter is derived for image enhancement. The main object of this filter is to improve the output image of a linear spatially invariant image restoration filter such as Wiener filter. In this filter the processing for flat fields of image gray levels is quite different from that of edge portions of the image. As a new trial we apply one-dimensional smoothing to the edge portions. This is because it would be important that the edge line of an image is linked smoothly for our visual perception. For flat fields we divide these into three categories, 'full flat field', 'ordinary flat field', and 'less flat field'. In each field the unknown parameter of the new smoothing filter is determined optimally. The resulting smoothed image is more preferable for human eye.
ER -
English
