论文标题
恢复数字图像中DCT系数的符号位作为优化问题
Recovering Sign Bits of DCT Coefficients in Digital Images as an Optimization Problem
论文作者
论文摘要
在DCT系数中恢复未知，缺失，损坏，扭曲或丢失的信息是数字图像处理的多个应用程序中的常见任务，包括图像压缩，选择性图像加密和图像通信。本文通过提出两种不同的近似方法来解决混合整数线性编程（MILP）问题，该方法研究了数字图像的DCT系数中的符号位，这通常是NP-HARD。一种方法是将MILP问题放松到线性编程（LP）问题，而另一种方法将原始的MILP问题分为一些较小的MILP问题和LP问题。我们考虑了如何将所提出的方法应用于JPEG编码的图像，并进行了广泛的实验以验证其性能。实验结果表明，根据客观质量指标和我们的主观评估，所提出的方法的表现优于其他现有方法。
Recovering unknown, missing, damaged, distorted, or lost information in DCT coefficients is a common task in multiple applications of digital image processing, including image compression, selective image encryption, and image communication. This paper investigates the recovery of sign bits in DCT coefficients of digital images, by proposing two different approximation methods to solve a mixed integer linear programming (MILP) problem, which is NP-hard in general. One method is a relaxation of the MILP problem to a linear programming (LP) problem, and the other splits the original MILP problem into some smaller MILP problems and an LP problem. We considered how the proposed methods can be applied to JPEG-encoded images and conducted extensive experiments to validate their performances. The experimental results showed that the proposed methods outperformed other existing methods by a substantial margin, both according to objective quality metrics and our subjective evaluation.
