Learning to Remove Wrinkled Transparent Film with Polarized Prior

• URL: http://arxiv.org/abs/2403.04368v1
• Date: Thu, 7 Mar 2024 09:56:56 GMT
• Title: Learning to Remove Wrinkled Transparent Film with Polarized Prior
• Authors: Jiaqi Tang, Ruizheng Wu, Xiaogang Xu, Sixing Hu and Ying-Cong Chen
• Abstract summary: Film Removal (FR) attempts to remove the interference of wrinkled transparent films and reconstruct the original information under films for industrial recognition systems. We build a practical dataset with polarization information containing paired data with and without transparent film. We aim to remove interference from the film (specular highlights and other degradations) with an end-to-end framework.
• Score: 33.56569839317172
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: In this paper, we study a new problem, Film Removal (FR), which attempts to remove the interference of wrinkled transparent films and reconstruct the original information under films for industrial recognition systems. We first physically model the imaging of industrial materials covered by the film. Considering the specular highlight from the film can be effectively recorded by the polarized camera, we build a practical dataset with polarization information containing paired data with and without transparent film. We aim to remove interference from the film (specular highlights and other degradations) with an end-to-end framework. To locate the specular highlight, we use an angle estimation network to optimize the polarization angle with the minimized specular highlight. The image with minimized specular highlight is set as a prior for supporting the reconstruction network. Based on the prior and the polarized images, the reconstruction network can decouple all degradations from the film. Extensive experiments show that our framework achieves SOTA performance in both image reconstruction and industrial downstream tasks. Our code will be released at \url{https://github.com/jqtangust/FilmRemoval}.

Related papers

• Improving Lens Flare Removal with General Purpose Pipeline and Multiple Light Sources Recovery [69.71080926778413]
  flare artifacts can affect image visual quality and downstream computer vision tasks. Current methods do not consider automatic exposure and tone mapping in image signal processing pipeline. We propose a solution to improve the performance of lens flare removal by revisiting the ISP and design a more reliable light sources recovery strategy.
  arXiv  Detail & Related papers  (2023-08-31T04:58:17Z)
• Neural Image Re-Exposure [86.42475408644822]
  An improper shutter may lead to a blurry image, video discontinuity, or rolling shutter artifact. We propose a neural network-based image re-exposure framework. It consists of an encoder for visual latent space construction, a re-exposure module for aggregating information to neural film with a desired shutter strategy, and a decoder for 'developing' neural film into a desired image.
  arXiv  Detail & Related papers  (2023-05-23T01:55:37Z)
• Bringing Old Films Back to Life [33.78936333249432]
  We present a learning-based framework, recurrent transformer network (RTN), to restore heavily degraded old films. Our method is based on the hidden knowledge learned from adjacent frames that contain abundant information about the occlusion.
  arXiv  Detail & Related papers  (2022-03-31T17:59:59Z)
• Zero-Reference Image Restoration for Under-Display Camera of UAV [10.498049147922258]
  We propose a new method to enhance the visual experience by enhancing the texture and color of images. Our method trains a lightweight network to estimate a low-rank affine grid on the input image. Our model can perform high-quality recovery of images of arbitrary resolution in real time.
  arXiv  Detail & Related papers  (2022-02-13T11:12:00Z)
• Removing Diffraction Image Artifacts in Under-Display Camera via Dynamic Skip Connection Network [80.67717076541956]
  Under-Display Camera (UDC) systems provide a true bezel-less and notch-free viewing experience on smartphones. In a typical UDC system, the pixel array attenuates and diffracts the incident light on the camera, resulting in significant image quality degradation. In this work, we aim to analyze and tackle the aforementioned degradation problems.
  arXiv  Detail & Related papers  (2021-04-19T18:41:45Z)
• Restoration of Video Frames from a Single Blurred Image with Motion Understanding [69.90724075337194]
  We propose a novel framework to generate clean video frames from a single motion-red image. We formulate video restoration from a single blurred image as an inverse problem by setting clean image sequence and their respective motion as latent factors. Our framework is based on anblur-decoder structure with spatial transformer network modules.
  arXiv  Detail & Related papers  (2021-04-19T08:32:57Z)
• Polarized Reflection Removal with Perfect Alignment in the Wild [66.48211204364142]
  We present a novel formulation to removing reflection from polarized images in the wild. We first identify the misalignment issues of existing reflection removal datasets. We build a new dataset with more than 100 types of glass in which obtained transmission images are perfectly aligned with input mixed images.
  arXiv  Detail & Related papers  (2020-03-28T13:29:31Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.