Advancements and Trends in Ultra-High-Resolution Image Processing: An Overview

• URL: http://arxiv.org/abs/2312.00250v1
• Date: Thu, 30 Nov 2023 23:47:37 GMT
• Title: Advancements and Trends in Ultra-High-Resolution Image Processing: An Overview
• Authors: Zhuoran Zheng, Boxue Xiao
• Abstract summary: In this paper, we introduce the current state of UHD image enhancement from two perspectives. One is the application field, the other is the technology.
• Score: 2.17172315573773
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Currently, to further improve visual enjoyment, Ultra-High-Definition (UHD) images are catching wide attention. Here, UHD images are usually referred to as having a resolution greater than or equal to $3840 \times 2160$. However, since the imaging equipment is subject to environmental noise or equipment jitter, UHD images are prone to contrast degradation, blurring, low dynamic range, etc. To address these issues, a large number of algorithms for UHD image enhancement have been proposed. In this paper, we introduce the current state of UHD image enhancement from two perspectives, one is the application field and the other is the technology. In addition, we briefly explore its trends.

Related papers

• Dropout the High-rate Downsampling: A Novel Design Paradigm for UHD Image Restoration [11.866565346920781]
  D2Net enables direct full-resolution inference on Ultra-high-definition (UHD) images. We show that our model achieves better quantitative and qualitative results than state-of-the-art methods.
  arXiv  Detail & Related papers  (2024-11-10T13:05:36Z)
• AIM 2024 Challenge on UHD Blind Photo Quality Assessment [49.54883484094671]
  The AIM 2024 UHD-IQA Challenge aims to advance the No-Reference Image Quality Assessment (NR-IQA) task for modern, high-resolution photos. The challenge is based on the recently released UHD-IQA Benchmark Database, which comprises 6,073 UHD-1 (4K) images annotated with perceptual quality ratings from expert raters.
  arXiv  Detail & Related papers  (2024-09-24T17:44:24Z)
• Assessing UHD Image Quality from Aesthetics, Distortions, and Saliency [51.36674160287799]
  We design a multi-branch deep neural network (DNN) to assess the quality of UHD images from three perspectives. aesthetic features are extracted from low-resolution images downsampled from the UHD ones. Technical distortions are measured using a fragment image composed of mini-patches cropped from UHD images. The salient content of UHD images is detected and cropped to extract quality-aware features from the salient regions.
  arXiv  Detail & Related papers  (2024-09-01T15:26:11Z)
• Ultra-High-Definition Image Restoration: New Benchmarks and A Dual Interaction Prior-Driven Solution [37.42524995828323]
  We construct UHD snow and rain benchmarks, named UHD-Snow and UHD-Rain. Each benchmark contains 3200 degraded/clear image pairs of 4K resolution. We propose an effective UHD image restoration solution by considering gradient and normal priors in model design.
  arXiv  Detail & Related papers  (2024-06-19T14:58:49Z)
• Towards Ultra-High-Definition Image Deraining: A Benchmark and An Efficient Method [42.331058889312466]
  This paper contributes the first large-scale UHD image deraining dataset, 4K-Rain13k, that contains 13,000 image pairs at 4K resolution. We develop an effective and efficient vision-based architecture (UDR-Mixer) to better solve this task.
  arXiv  Detail & Related papers  (2024-05-27T11:45:08Z)
• Benchmarking Ultra-High-Definition Image Reflection Removal [25.02234305857731]
  We propose a transformer-based architecture named RRFormer for reflection removal. We show that RRFormer achieves state-of-the-art performance on both the non-UHD dataset and our proposed UHDRR datasets.
  arXiv  Detail & Related papers  (2023-08-01T03:56:50Z)
• Embedding Fourier for Ultra-High-Definition Low-Light Image Enhancement [78.67036949708795]
  Ultra-High-Definition (UHD) photo has gradually become the standard configuration in advanced imaging devices. We propose a new solution, UHDFour, that embeds Fourier transform into a cascaded network. We also contribute the first real UHD LLIE dataset, textbfUHD-LL, that contains 2,150 low-noise/normal-clear 4K image pairs.
  arXiv  Detail & Related papers  (2023-02-23T07:43:41Z)
• Real-Time Under-Display Cameras Image Restoration and HDR on Mobile Devices [81.61356052916855]
  The images captured by under-display cameras (UDCs) are degraded by the screen in front of them. Deep learning methods for image restoration can significantly reduce the degradation of captured images. We propose a lightweight model for blind UDC Image Restoration and HDR, and we also provide a benchmark comparing the performance and runtime of different methods on smartphones.
  arXiv  Detail & Related papers  (2022-11-25T11:46:57Z)
• HDR-GAN: HDR Image Reconstruction from Multi-Exposed LDR Images with Large Motions [62.44802076971331]
  We propose a novel GAN-based model, HDR-GAN, for synthesizing HDR images from multi-exposed LDR images. By incorporating adversarial learning, our method is able to produce faithful information in the regions with missing content.
  arXiv  Detail & Related papers  (2020-07-03T11:42:35Z)

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.