边缘云中基于压缩感知的加密与认证测试数据集DIV2K

DIV2K 数据集是一个广泛应用于图像处理领域的高质量图像数据集，特别用于图像超分辨率、图像压缩和恢复等任务。该数据集包含2000张高分辨率图像，涵盖了各种不同的场景和内容，适用于多种计算机视觉算法的评估与测试。DIV2K 数据集的主要特点包括：1)高分辨率：数据集中的图像分辨率普遍为2K（2048 ×1080像素）及以上，确保了图像质量的高保真性，适合用于高精度图像处理任务。2)内容多样性：该数据集包括多种类型的图像，如自然风光、城市景观、建筑物、人物等，提供了丰富的场景背景，有助于对算法在不同环境下的表现进行评估。3)标准化基准：DIV2K 数据集已成为图像超分辨率领域的标准基准，广泛应用于算法的性能测试和比较，尤其在图像增强、重建和恢复任务中具有重要的参考价值。DIV2K 数据集包含 2,000 张高分辨率图像，图像分辨率为 2K（2048 × 1080 像素）及以上，分为训练集、验证集和测试集。具体组成如下：1)训练集：包含 800 张高分辨率（HR）图像，以及相应的低分辨率（LR）图像。训练集图像用于超分辨率算法的训练。2)验证集：包含 100 张高分辨率图像，以及相应的低分辨率图像。验证集用于在训练过程中评估模型性能。3)测试集：包含 100 张高分辨率图像，以及相应的低分辨率图像。测试集用于最终评估模型的泛化能力和性能。

The DIV2K dataset is a high-quality image dataset widely used in the field of image processing, particularly for tasks such as image super-resolution, image compression, and image restoration. This dataset contains 2000 high-resolution images covering diverse scenes and content, suitable for the evaluation and testing of various computer vision algorithms. The main characteristics of the DIV2K dataset are as follows: 1) High Resolution: The images in the dataset generally have a resolution of 2K (2048 × 1080 pixels) or higher, ensuring high fidelity of image quality and being suitable for high-precision image processing tasks. 2) Content Diversity: The dataset includes various types of images, such as natural landscapes, urban scenery, buildings, portraits, etc., providing rich scene backgrounds to facilitate the evaluation of algorithm performance in different environments. 3) Standardized Benchmark: The DIV2K dataset has become a standard benchmark in the field of image super-resolution, widely used for performance testing and comparison of algorithms, and holds important reference value especially in image enhancement, reconstruction and restoration tasks. The DIV2K dataset consists of 2,000 high-resolution images with a resolution of 2K (2048 × 1080 pixels) or higher, and is divided into training, validation and test sets. The specific composition is as follows: 1) Training Set: Contains 800 high-resolution (HR) images and their corresponding low-resolution (LR) images. The training set images are used for training super-resolution algorithms. 2) Validation Set: Contains 100 high-resolution images and their corresponding low-resolution images. The validation set is used to evaluate model performance during the training process. 3) Test Set: Contains 100 high-resolution images and their corresponding low-resolution images. The test set is used for the final evaluation of model generalization ability and performance.

搜集汇总

背景与挑战

背景概述

该数据集是DIV2K，一个在边缘云计算环境中用于基于压缩感知的加密与认证测试的高质量图像集合。它包含2000张高分辨率图像，分辨率达2K及以上，覆盖多样场景，适用于图像超分辨率、压缩和恢复等任务，并分为训练、验证和测试集。