Paper Info
Title
Adaptive guided image filtering for sharpness enhancement and noise reduction
Abstract
Sharpness enhancement and noise reduction play crucial roles in computer vision and image processing. The problem is to enhance the appearance and reduce the noise of the digital images without causing halo artifacts. In this paper, we propose an adaptive guided image filtering (AGF) able to perform halo-free edge slope enhancement and noise reduction simulaneously. The proposed method is developed based on guided image filtering (GIF) and the shift-variant technique, part of adaptive bilateral filtering (ABF). Experiments showed the results produced from our method are superior to those produced from unsharp masking-based techniques and comparable to ABF filtered output. Our proposed AGF outperforms ABF in terms of computational complexity. It is implemented using a fast and exact linear-time algorithm.
Year
DOI
Venue
2011
10.1007/978-3-642-25367-6_29
PSIVT (1)
Keywords
Field
DocType
halo-free edge slope enhancement,digital image,computer vision,noise reduction simulaneously,image processing,sharpness enhancement,computational complexity,proposed agf,noise reduction
Unsharp masking,Noise reduction,Computer vision,Median filter,Pattern recognition,Computer science,Filter (signal processing),Digital image,Artificial intelligence,Bilateral filter,Computational complexity theory,Edge-preserving smoothing
Conference
Volume
ISSN
Citations 
7087
0302-9743
9
PageRank 
References 
Authors
0.54
16
3
Name
Order
Citations
PageRank
Cuong Cao Pham1836.00
Synh Viet Uyen Ha2183.76
Jae Wook Jeon356577.35