图像增强的改进中值滤波数据嵌入方法

Koi Yee Ng, Simying Ong, Koksheik Wong
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摘要

本文提出了一种改进的数据嵌入方法,通过中值滤波器的概念在嵌入数据的同时进行图像增强。在预定窗口大小内的像素被收集和排序,以获得数据表示感兴趣的分区。中心像素将以滑动窗口的方式替换为待嵌入的数据,直到像素被替换。然而,嵌入后像素值的修改给数据提取带来了挑战。在这项工作中,测试了各种数据提取方法,包括在数据提取过程中以滑动窗口方式使用中值滤波器进行修复,以及反向方式进行修复,以了解它们对图像质量和数据提取精度的影响。此外,通过实施多数投票,显著提高了数据提取的准确性。使用BSDS300数据集进行实验,观察到图像质量平均可提高9.5%,数据提取精度平均可提高7.7%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Improved Median-Filtered Data Embedding Method for Image Enhancement
This paper proposes an improvement for a data embedding method to embed the data while performing image enhancements via the concept of Median Filter. The pixels within a predetermined window size are gathered and sorted to obtain the partitions of interest for data representation. The centre pixels will be replaced with the to-be-embedded data in a sliding window manner until pixels are replaced. However, the modification of pixel values after the embedding process makes the data extraction process challenging. In this work, various data extraction methods are tested, including repairing using median filter during data extraction in a sliding window manner, and the reverse manner to understand their effects on the image quality and data extraction accuracy. In addition, by implementing majority vote, the data extraction accuracy is significantly improved. The experiment is conducted using the BSDS300 dataset, and it is observed that the image quality can be improved up to 9.5% while the data extraction accuracy is improved up to 7.7%, averagely.
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