一种安全的多帧遥感图像的外包融合去噪方案

遥感图像去噪是图像处理领域的热门研究课题.伴随着采集设备改进和技术提升, 同一场景下的多帧图像的融合去噪已经成为可能.然而海量遥感图像去噪在单机上暴露出处理速度慢、并发性差等问题，利用云计算平台进行海量数据的存储和处理是大势所趋.为保护外包计算的遥感图像的安全性，提出了一种针对多帧遥感图像的安全外包融合去噪方案.方案利用Paillier加密算法的密文加法同态性和Johnson-Lindenstrauss转换近似保留欧氏距离的特性，对平均图像进行基于动态滤波参数的融合去噪.选用从多幅Landsat 8遥感图像中截取多个512×512像素的图像作为实验对象，搭建了Spark单机环境来模拟云环境.实验数据表明:提出的外包方案可以有效地保证遥感图像的安全性；同时，融合去噪方案的效果明显优于已有的密文去噪方案和单帧密文去噪方案，且对不同图像、不同大小的噪声均有很好的去噪效果.

A Secure Outsourced Fusion Denoising Scheme in Multiple Encrypted Remote Sensing Images

Remote sensing image denoising is a hot research topic in the field of image processing. The improvement of remote sensing image acquisition equipment and technology has made it possible to collect multiple images from the same scene in a short period of time. However, the processing huge number of the remote sensing images on the ordinary computers has caused the low processing capability and poor concurrency. It is a trend to store and compute the big data outsourced to the cloud. To protect the security of outsourced remote sensing images, the article presents a secure outsourced fusion denoising scheme in multiple encrypted remote sensing images to implement the fusion denoising based on dynamic filtering parameters. In the schemes, the ciphertext from Johnson-Lindenstrauss transform is used to weight calculatation as well as the plaintext and the ciphertext from Paillier homomorphic encryption is used to fusion denoise by the linear calculation of ciphertext. The experiments use several 512×512 pixels remote sensing images based on the Spark alone-server environment to simulate the cloud platform. The experimental results show that the outsourcing schemes can effectively ensure the security of the remote sensing images and get better denoising quality with different sizes of noise than the existing schemes.