Abstract Large view stereoscopic images can provide users with immersive depth experience. Image stitching techniques aim to obtain large view stitched images, and there have been various image stitching algorithms proposed recently. However, there is still no effective objective quality assessment for stereoscopic stitched images. In this paper, we propose a new perceptual objective stereoscopic stitched image quality assessment (S-SIQA) method by considering different distortion types in the existing stitching methods, including color distortion, ghost distortion, structure distortion(shape distortion, information loss), and disparity distortion. The quality evaluation methods for these distortion types are designed by using the color difference coefficient, points distance, matched line inclination degree, information loss, and disparity difference. Then we fuse these measures in the proposed S-SIQA model by an optimally weighted linear combination. In addition, to evaluate the performance of the proposed S-SIQA, we build a subjective quality assessment database for stereoscopic stitched images. Experimental results have confirmed the proposed method can effectively measure the perceptual quality of stereoscopic stitched images.

中文翻译：

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立体拼接图像的感知客观质量评估

摘要 大视野立体图像可以为用户提供身临其境的深度体验。图像拼接技术旨在获得大视图拼接图像，最近提出了各种图像拼接算法。然而，对于立体拼接图像仍然没有有效的客观质量评估。在本文中，我们通过考虑现有拼接方法中的不同失真类型，提出了一种新的感知客观立体拼接图像质量评估（S-SIQA）方法，包括颜色失真、重影失真、结构失真（形状失真、信息丢失）和视差失真。这些畸变类型的质量评价方法是利用色差系数、点距、匹配线倾斜度、信息丢失、和视差。然后我们通过最佳加权线性组合在所提出的 S-SIQA 模型中融合这些度量。此外，为了评估所提出的 S-SIQA 的性能，我们为立体拼接图像构建了一个主观质量评估数据库。实验结果证实了所提出的方法可以有效地测量立体拼接图像的感知质量。