Sub-window Box Filter

Yuanhao Gong; Bozhi Liu; Xianxu Hou; Guoping Qiu

doi:10.1109/VCIP.2018.8698682

Sub-window Box Filter

Yuanhao Gong, Bozhi Liu, Xianxu Hou, Guoping Qiu

Shenzhen University

Research output: Chapter in Book or Report/Conference proceeding › Conference Proceeding › peer-review

17 Citations (Scopus)

Abstract

Box filter is a fundamental filter in image processing. However, it can not preserve edges or corners. In this paper, we present a simple but novel method that can make box filter both edge and corner preserving. More specifically, we combine the box filter with sub-window regression to achieve this task. This filter inherits some properties from box filter, such as O(1) running time with respect to the window radius. After analyzing its parameters, we show its corner and edge preserving property on real images and compare it with Guided filter.

Original language	English
Title of host publication	VCIP 2018 - IEEE International Conference on Visual Communications and Image Processing
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781538644584
DOIs	https://doi.org/10.1109/VCIP.2018.8698682
Publication status	Published - 2 Jul 2018
Externally published	Yes
Event	33rd IEEE International Conference on Visual Communications and Image Processing, VCIP 2018 - Taichung, Taiwan, Province of China Duration: 9 Dec 2018 → 12 Dec 2018

Publication series

Name	VCIP 2018 - IEEE International Conference on Visual Communications and Image Processing

Conference

Conference	33rd IEEE International Conference on Visual Communications and Image Processing, VCIP 2018
Country/Territory	Taiwan, Province of China
City	Taichung
Period	9/12/18 → 12/12/18

Keywords

Box filter
Curvature filter
Edge preserving
Sub window
Sub window regression

Access to Document

10.1109/VCIP.2018.8698682

Cite this

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title = "Sub-window Box Filter",

abstract = "Box filter is a fundamental filter in image processing. However, it can not preserve edges or corners. In this paper, we present a simple but novel method that can make box filter both edge and corner preserving. More specifically, we combine the box filter with sub-window regression to achieve this task. This filter inherits some properties from box filter, such as O(1) running time with respect to the window radius. After analyzing its parameters, we show its corner and edge preserving property on real images and compare it with Guided filter.",

keywords = "Box filter, Curvature filter, Edge preserving, Sub window, Sub window regression",

author = "Yuanhao Gong and Bozhi Liu and Xianxu Hou and Guoping Qiu",

note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 33rd IEEE International Conference on Visual Communications and Image Processing, VCIP 2018 ; Conference date: 09-12-2018 Through 12-12-2018",

year = "2018",

month = jul,

day = "2",

doi = "10.1109/VCIP.2018.8698682",

language = "English",

series = "VCIP 2018 - IEEE International Conference on Visual Communications and Image Processing",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

booktitle = "VCIP 2018 - IEEE International Conference on Visual Communications and Image Processing",

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Gong, Y, Liu, B, Hou, X & Qiu, G 2018, Sub-window Box Filter. in VCIP 2018 - IEEE International Conference on Visual Communications and Image Processing., 8698682, VCIP 2018 - IEEE International Conference on Visual Communications and Image Processing, Institute of Electrical and Electronics Engineers Inc., 33rd IEEE International Conference on Visual Communications and Image Processing, VCIP 2018, Taichung, Taiwan, Province of China, 9/12/18. https://doi.org/10.1109/VCIP.2018.8698682

Sub-window Box Filter. / Gong, Yuanhao; Liu, Bozhi; Hou, Xianxu et al.
VCIP 2018 - IEEE International Conference on Visual Communications and Image Processing. Institute of Electrical and Electronics Engineers Inc., 2018. 8698682 (VCIP 2018 - IEEE International Conference on Visual Communications and Image Processing).

Research output: Chapter in Book or Report/Conference proceeding › Conference Proceeding › peer-review

TY - GEN

T1 - Sub-window Box Filter

AU - Gong, Yuanhao

AU - Liu, Bozhi

AU - Hou, Xianxu

AU - Qiu, Guoping

PY - 2018/7/2

Y1 - 2018/7/2

N2 - Box filter is a fundamental filter in image processing. However, it can not preserve edges or corners. In this paper, we present a simple but novel method that can make box filter both edge and corner preserving. More specifically, we combine the box filter with sub-window regression to achieve this task. This filter inherits some properties from box filter, such as O(1) running time with respect to the window radius. After analyzing its parameters, we show its corner and edge preserving property on real images and compare it with Guided filter.

AB - Box filter is a fundamental filter in image processing. However, it can not preserve edges or corners. In this paper, we present a simple but novel method that can make box filter both edge and corner preserving. More specifically, we combine the box filter with sub-window regression to achieve this task. This filter inherits some properties from box filter, such as O(1) running time with respect to the window radius. After analyzing its parameters, we show its corner and edge preserving property on real images and compare it with Guided filter.

KW - Box filter

KW - Curvature filter

KW - Edge preserving

KW - Sub window

KW - Sub window regression

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U2 - 10.1109/VCIP.2018.8698682

DO - 10.1109/VCIP.2018.8698682

M3 - Conference Proceeding

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T3 - VCIP 2018 - IEEE International Conference on Visual Communications and Image Processing

BT - VCIP 2018 - IEEE International Conference on Visual Communications and Image Processing

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 33rd IEEE International Conference on Visual Communications and Image Processing, VCIP 2018

Y2 - 9 December 2018 through 12 December 2018

ER -

Sub-window Box Filter

Abstract

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Conference

Keywords

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