Fast multiple-view denoising based on image reconstruction by plane sweeping

Denoising is important in image processing because degradation by noise affects not only the quality of captured images but also the performance of visual applications that use them. For example, under low light levels, it is difficult to accurately estimate scene depths using noisy stereo images. Conventional methods for denoising find similar regions on an image or among multiple images by block matching(BM) to integrate them for suppressing noise effectively. However, such exhaustive BM incurs considerable costs for real-time applications, in particular, when multi-view images(MVI) are involved. We use view-dependent plane sweeping(PS) for image reconstruction to achieve effective MVI denoising with low computational cost. We use PS for converting MVI to multi-focus images(MFI) to suppress their noise. Then, we find regions in focus on the MFI solely by comparing them with the target view image. Finally, we simply merge the regions to obtain reconstructed images in which their noise is effectively suppressed.