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  • Adaptive bilateral filtering using saliency map for deblocking low bit rate videos

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    Tjondronegoro224582-Accepted.pdf (438.2Kb)
    Author(s)
    Himawan, I
    Zele, AJ
    Tjondronegoro, D
    Griffith University Author(s)
    Tjondronegoro, Dian W.
    Year published
    2014
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    Abstract
    This paper proposes a novel approach to video deblocking which performs perceptually adaptive bilateral filtering by considering color, intensity, and motion features in a holistic manner. The method is based on bilateral filter which is an effective smoothing filter that preserves edges. The bilateral filter parameters are adaptive and avoid over-blurring of texture regions and at the same time eliminate blocking artefacts in the smooth region and areas of slow motion content. This is achieved by using a saliency map to control the strength of the filter for each individual point in the image based on its perceptual importance. ...
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    This paper proposes a novel approach to video deblocking which performs perceptually adaptive bilateral filtering by considering color, intensity, and motion features in a holistic manner. The method is based on bilateral filter which is an effective smoothing filter that preserves edges. The bilateral filter parameters are adaptive and avoid over-blurring of texture regions and at the same time eliminate blocking artefacts in the smooth region and areas of slow motion content. This is achieved by using a saliency map to control the strength of the filter for each individual point in the image based on its perceptual importance. The experimental results demonstrate that the proposed algorithm is effective in deblocking highly compressed video sequences and to avoid over-blurring of edges and textures in salient regions of image.
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    Conference Title
    2014 IEEE International Conference on Multimedia and Expo (ICME)
    DOI
    https://doi.org/10.1109/ICME.2014.6890173
    Copyright Statement
    © 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
    Subject
    Artificial Intelligence and Image Processing
    Publication URI
    http://hdl.handle.net/10072/390268
    Collection
    • Conference outputs

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