The quick and high quality image interpolation for single image using multi-filtering and weighted mean

Takuro Yamaguchi, Masaaki Ikehara

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    3 Citations (Scopus)

    Abstract

    Image upsampling from one input image gathers considerable attention in the field of computer vision. The problem is ill-posed because the number of known low-resolution (LR) pixels is less than that of unknown high-resolution (HR) pixels. Therefore, quality of an upsampled image depends on prior assumptions. Image interpolation methods are one of the image upsampling technologies and are faster than other image upsampling technologies such as Super-Resolution. However, these methods tend to cause jaggies and blurs in edge and texture regions. We use the idea of Multi-surface Fitting (MF) to solve these problems. MF uses plural local functions to estimate an HR pixel and it reduces blurs. Moreover, we utilize filtering instead of calculation of each local function in order to reduce a computational cost. And we introduce new weights to estimate edge directions. By these ideas, our method has both high quality and a low computational cost.

    Original languageEnglish
    Title of host publication2016 IEEE International Conference on Image Processing, ICIP 2016 - Proceedings
    PublisherIEEE Computer Society
    Pages2841-2845
    Number of pages5
    Volume2016-August
    ISBN (Electronic)9781467399616
    DOIs
    Publication statusPublished - 2016 Aug 3
    Event23rd IEEE International Conference on Image Processing, ICIP 2016 - Phoenix, United States
    Duration: 2016 Sep 252016 Sep 28

    Other

    Other23rd IEEE International Conference on Image Processing, ICIP 2016
    CountryUnited States
    CityPhoenix
    Period16/9/2516/9/28

    Keywords

    • Filtering
    • Image interpolation
    • Multi-surface fitting
    • Weighted mean

    ASJC Scopus subject areas

    • Software
    • Computer Vision and Pattern Recognition
    • Signal Processing

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