Global motion greatly increases the number of false alarms for object detection in video sequences against dynamic backgrounds. Therefore, before detecting the target in the …
In recent years, deep neural network-based restoration methods have achieved state-of-the- art results in various image deblurring tasks. However, one major drawback of deep learning …
L Wang, H Wu, D Sun, Y Yan - Measurement, 2023 - Elsevier
Visual dimension measurement is commonly required in industrial detection. However, monocular vision measurements have a low accuracy with large field of view (FOV), while …
P Kandula - arXiv preprint arXiv:2112.06175, 2021 - arxiv.org
In the literature, coarse-to-fine or scale-recurrent approach ie progressively restoring a clean image from its low-resolution versions has been successfully employed for single image …
Supervised networks address the task of low-light enhancement using paired images. However, collecting a wide variety of low-light/clean paired images is tedious as the scene …
Satellite images are typically subject to multiple distortions. Different factors affect the quality of satellite images, including changes in atmosphere, surface reflectance, sun illumination …
Several supervised networks exist that remove haze information from underwater images using paired datasets and pixel-wise loss functions. However, training these networks …
In this paper, we address the problem of dynamic scene deblurring in the presence of motion blur. Restoration of images affected by severe blur necessitates a network design …
We present a solution for the goal of extracting a video from a single motion blurred image to sequentially reconstruct the clear views of a scene as beheld by the camera during the time …