Lossless JPEG

About: Lossless JPEG is a research topic. Over the lifetime, 2415 publications have been published within this topic receiving 51110 citations. The topic is also known as: Lossless JPEG & .jls.

Analysis and Cryptanalysis of a Selective Encryption Method for JPEG Images

Abstract: This paper addresses the protection of images. We address the problem of simultaneous selective encryption (SE) and image compression. The SE is done by using the Advanced Encryption Standard (AES) algorithm with the Cipher Feedback (CFB) mode one a part of the Huffman coefficients corresponding to the AC frequencies. For the compression we consider the JPEG algorithm. Our approach is done without affecting the compression rate and by keeping the JPEG bitstream compliance. In the proposed method, the SE is performed in the Huffman coding stage of the JPEG algorithm without affecting the size of the compressed image. We provide an experimental analysis of the proposed method when applied on still images as well as the results when applying SE in JPEG compressed images.

Alpha-trimmed image estimation for JPEG steganography detection

Abstract: In information security, steganalysis has been an important topic since evidences first indicated steganography has been used for covert communication. Among all digital files, numerous devices generate JPEG images due to the capability of compression and compatibility. A large number of JPEG steganography methods are also provided online for free usage. This has spawned significant research in the area of JPEG steganalysis. This paper introduces an image estimation technique utilizing the alpha-trimmed mean for distinguishing clean and steganography images. The hidden information is considered additive noise to the image. The alpha-trimmed method estimates steganographic messages within images in the spatial domain and provide flexibility for classifying various steganography methods in the JPEG compression domain. For three JPEG steganography methods along with three embedding message files applied to an image data set, the proposed method results in better separability between clean and steganographic classes. The results are based on comparisons between the presented method and two existing methods in which classification accuracies are increased by as much as 32%.

Detecting Double Compressed JPEG Images by Using Moment Features of Mode Based DCT Histograms

Abstract: The double compression of JPEG images is one of the important evidences of image tampering. The paper proposes a novel passive double compressed JPEG image detection algorithm using the moment features of the modes based DCT histogram's characteristic function. Support vector machine is used as the classifier. Experimental results demonstrate that the proposed algorithm significantly increases the detection accuracy when the first compressing quality factor is large such as 95. In order to further improve the overall detection accuracy of double compressed JPEG in various quality factors, the paper proposes an improved algorithm by combing the moment features with the Mode Based Fist Digit features (MBFDF). The experimental results show that the overall detection accuracies can be further improved and the proposed algorithm outperforms some traditional methods, especially when the first compressing quality factor is large such as 95.

Reliable JPEG 2000 wireless imaging by means of error-correcting MQ coder

Abstract: A new error resilience tool is proposed for robust JPEG 2000 imaging over noisy channels. In particular, a modified encoder, based on an MQ arithmetic coder with forbidden symbol, is introduced, along with a maximum likelihood error-correcting MQ decoder. The proposed technique features error detection, error concealment and error correction capability, thus adding new useful functionalities to JPEG 2000. Experimental results show that this technique largely outperforms the standard JPEG 2000 error resilience tools for error concealment and hard/soft channel decoding.

Lossless data compression for infrared hyperspectral sounders: an update

Abstract: The compression of hyperspectral sounder data is beneficial for more efficient archive and transfer given its large 3-D volume. Moreover, since physical retrieval of geophysical parameters from hyperspectral sounder data is a mathematically ill-posed problem that is sensitive to the error of the data, lossless or near-lossless compression is desired. This paper provides an update into applications of state-of-the-art 2D and 3D lossless compression algorithms such as 3D EZW, 3D SPIHT, 2D JPEG2000, 2D JPEG-LS and 2D CALIC for hyperspectral sounder data. In addition, in order to better explore the correlations between the remote spectral regions affected by the same type of atmospheric absorbing constituents or clouds, the Bias-Adjusted Reordering (BAR) scheme is presented which reorders the data such that the bias-adjusted distance between any two neighboring vectors is minimized. This scheme coupled with any of the state-of-the-art compression algorithms produces significant compression gains.