Performing scalable lossy compression on pixel encrypted images

Abstract

Compression of encrypted data draws much attention in recent years due to the security concerns in a service-oriented environment such as cloud computing. We propose a scalable lossy compression scheme for images having their pixel value encrypted with a standard stream cipher. The encrypted data are simply compressed by transmitting a uniformly subsampled portion of the encrypted data and some bitplanes of another uniformly subsampled portion of the encrypted data. At the receiver side, a decoder performs content-adaptive interpolation based on the decrypted partial information, where the received bit plane information serves as the side information that reflects the image edge information, making the image reconstruction more precise. When more bit planes are transmitted, higher quality of the decompressed image can be achieved. The experimental results show that our proposed scheme achieves much better performance than the existing lossy compression scheme for pixel-value encrypted images and also similar performance as the state-of-the-art lossy compression for pixel permutation-based encrypted images. In addition, our proposed scheme has the following advantages: at the decoder side, no computationally intensive iteration and no additional public orthogonal matrix are needed. It works well for both smooth and texture-rich images.

Scalable Compression of Stream Cipher Encrypted Images Through Context-Adaptive Sampling

“…The way of obtaining h t 's can also be regarded as a process of on-line learning the image local characteristics over the encrypted domain. In contrast, in the existing schemes [11], [14], the base layer coding and the enhancement layer coding are independently carried out, wasting the valuable information gained in the base layer.…”

“…Kang et. al later proposed an interpolation-based method for recovering compressed encrypted images, where compression is achieved by down-sampling and bit-plane decomposition [14]. We also devised a high-performance compression system for encrypted images, achieving nearly the same compression efficiency as a conventional image codec taking original, unencrypted images as input [15].…”

A new encryption-then-compression algorithm using the rate–distortion optimization

“…Recently, Zhang et al constructed a novel ETC system, which generates the auxiliary information as well as the stream-cipher encrypted image at the content owner side for improving the performance of compression and reconstruction [18]. Besides the CS and quantization, the down-sampling technique is also adopted for data reduction [19][20][21].…”

“…To obtain higher compression ratios with feasible reconstruction quality, lossy compression of encrypted data has also been studied so far [12][13][14][15][16][17][18][19][20][21]. In [12], Kumar and Makur employed the compressive sensing (CS) [22,23] technique to compress the encrypted image and then reconstruct the original image by modifying the basis pursuit algorithm.…”

Review of Image Compression and Encryption Techniques

“…Kang et al [12] proposed the application of lossy scalable compression technique after cryptographic process using standard stream cipher method. The values of image pixels that have been encrypted with standard a stream cipher are then put into the compression process by sending subsamples and bit planes.…”