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    This study introduces Reference-based Iterative Interaction (RIISSR) for stereo image super-resolution (SSR). RIISSR enhances stereo image quality by leveraging cross-view and cross-resolution correspondences for improved results.

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    Area of Science:

    • Computer Vision
    • Image Processing

    Background:

    • Stereo Image Super-Resolution (SSR) aims to enhance image quality by utilizing information from both left and right views.
    • Existing SSR methods often overlook the benefit of using a high-quality image from one view to improve the super-resolution of the other view.
    • Accurate correspondences are crucial for effective SSR, especially in textured regions.

    Purpose of the Study:

    • To propose a novel method, Reference-based Iterative Interaction (RIISSR), for improving stereo image super-resolution.
    • To exploit both pixel-wise and patch-wise matching strategies for establishing cross-view and cross-resolution correspondences.
    • To enhance the utilization of complementary information between stereo views for superior SSR performance.

    Main Methods:

    • RIISSR employs a P²-Matching strategy for iterative pixel-wise and patch-wise matching to establish correspondences.
    • An Information Perception Block (IPB) is designed to extract hierarchical contextualized features from different stereo views.
    • Pixel-wise matching is integrated within parallel IPBs for LR cross-view interaction, followed by iterative patch-wise matching using the SR stereo pair as a reference.

    Main Results:

    • The proposed RIISSR method demonstrates superior performance compared to existing state-of-the-art SSR techniques.
    • The P²-Matching strategy effectively establishes cross-view and cross-resolution correspondences, leading to enhanced SR quality.
    • The supervised side-out modulator (SSOM) effectively bridges pixel-wise and patch-wise matching mechanisms.

    Conclusions:

    • RIISSR offers a significant advancement in stereo image super-resolution by effectively utilizing inter-view and cross-resolution information.
    • The iterative interaction approach, combining pixel-wise and patch-wise matching, proves highly effective for SSR.
    • The method successfully addresses the limitations of previous SSR approaches by leveraging mutual referencing between stereo views.