Iterative range-domain weighted filter for structural preserving image smoothing and de-noising

The filtering weights from both spatial domain and range domain in the bilateral filtering always restrict filtering output value highly related to very close neighboring pixels, which results in very small changes before and after filtering. In order to better resolve the problem of piece-wise smoo...

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Bibliographic Details
Published in:Multimedia tools and applications 2019-01, Vol.78 (1), p.47-74
Main Authors: Zhao, Lijun, Bai, Huihui, Wang, Anhong, Zhao, Yao
Format: Article
Language:English
Subjects:
Algorithms
Computer Communication Networks
Computer Science
Data Structures and Information Theory
Image coding
Image filters
Methods
Multimedia Information Systems
Noise
Optimization
Pixels
Smoothing
Smoothness
Special Purpose and Application-Based Systems
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Summary:The filtering weights from both spatial domain and range domain in the bilateral filtering always restrict filtering output value highly related to very close neighboring pixels, which results in very small changes before and after filtering. In order to better resolve the problem of piece-wise smoothness image’s de-noising, such as artifact removal of compressed depth image, we firstly propose an iterative range-domain weighted filter method. The filtering weights of the proposed method are calculated within a fixed window in an iterative way according to both pixel similarity in the range domain and image’s pixel occurring frequency, but there is no filtering weight from the spatial domain. Secondly, the proposed method is combined with Gaussian filtering as an engine in order to finish the task of image smoothing, because image smoothing for extracting structures is often sensitive to image’s fine details with strong gradients during suppressing image’s textures. To demonstrate the efficiency, we have applied the proposed method into many applications. For example, the proposed method has better performances on compressed depth artifact removal than BF, CVBF, and ADTF. Meanwhile, the proposed method is used for capture-noise removal of depth image. Additionally, the proposed method performs better performance on structural information preservation for image smoothing, as compared to several existing methods.
ISSN:1380-7501
1573-7721
DOI:10.1007/s11042-017-5253-1