Self‐recovery is a tamper‐detection and image recovery methods based on data hiding. It generates two types of data and embeds them into the original image: authentication data for tamper detection and reference data for image recovery. In this paper, a region‐based scalable self‐recovery (RSS) method is proposed for salient‐object images. As the images consist of two main regions, the region of interest (ROI) and the region of non‐interest (RONI), the proposed method is aimed at achieving higher reconstruction quality for the ROI. Moreover, tamper tolerability is improved by using scalable recovery. In the RSS method, separate reference data are generated for the ROI and RONI. Initially, two compressed bitstreams at different rates are generated using the embedded zero‐block coding source encoder. Subsequently, each bitstream is divided into several parts, which are protected through various redundancy rates, using the Reed‐Solomon channel encoder. The proposed method is tested on 10 000 salient‐object images from the MSRA database. The results show that the RSS method, compared to related methods, improves reconstruction quality and tamper tolerability by approximately 30% and 15%, respectively.

中文翻译：

---

针对显着对象图像的基于区域的可扩展自我恢复

自我恢复是一种基于数据隐藏的篡改检测和图像恢复方法。它生成两种类型的数据并将其嵌入到原始图像中：用于篡改检测的身份验证数据和用于图像恢复的参考数据。本文针对显着目标图像提出了一种基于区域的可扩展自恢复（RSS）方法。由于图像由两个主要区域组成，即感兴趣区域（ROI）和非感兴趣区域（RONI），因此该方法旨在实现更高的ROI重建质量。此外，通过使用可伸缩恢复来提高篡改容忍度。在RSS方法中，将为ROI和RONI生成单独的参考数据。最初，使用嵌入式零块编码源编码器生成了不同速率的两个压缩比特流。随后，每个比特流都分成几个部分，使用Reed-Solomon信道编码器通过各种冗余率进行保护。在来自MSRA数据库的10000个显着目标图像上测试了该方法。结果表明，与相关方法相比，RSS方法分别将重建质量和篡改耐受性分别提高了30％和15％。