JPEG

About: JPEG is a research topic. Over the lifetime, 9980 publications have been published within this topic receiving 199206 citations. The topic is also known as: continuous-tone still image encoding & continuous-tone still image decoding.

Lossless data embedding--new paradigm in digital watermarking

Abstract: One common drawback of virtually all current data embedding methods is the fact that the original image is inevitably distorted due to data embedding itself. This distortion typically cannot be removed completely due to quantization, bit-replacement, or truncation at the grayscales 0 and 255. Although the distortion is often quite small and perceptual models are used to minimize its visibility, the distortion may not be acceptable for medical imagery (for legal reasons) or for military images inspected under nonstandard viewing conditions (after enhancement or extreme zoom). In this paper, we introduce a new paradigm for data embedding in images (lossless data embedding) that has the property that the distortion due to embedding can be completely removed from the watermarked image after the embedded data has been extracted. We present lossless embedding methods for the uncompressed formats (BMP, TIFF) and for the JPEG format. We also show how the concept of lossless data embedding can be used as a powerful tool to achieve a variety of nontrivial tasks, including lossless authentication using fragile watermarks, steganalysis of LSB embedding, and distortion-free robust watermarking.

An overview of the JPEG2000 still image compression standard

Abstract: In 1996, the JPEGcommittee began to investigate possibilities for a new still image compression standard to serve current and future applications. This initiative, which was named JPEG2000, has resulted in a comprehensive standard (ISO 154447ITU-T Recommendation T.800) that is being issued in six parts. Part 1, in the same vein as the JPEG baseline system, is aimed at minimal complexity and maximal interchange and was issued as an International Standard at the end of 2000. Parts 2–6 define extensions to both the compression technology and the file format and are currently in various stages of development. In this paper, a technical description of Part 1 of the JPEG2000 standard is provided, and the rationale behind the selected technologies is explained. Although the JPEG2000 standard only specifies the decoder and the codesteam syntax, the discussion will span both encoder and decoder issues to provide a better understanding of the standard in various applications. r 2002 Elsevier Science B.V. All rights reserved.

Defending against statistical steganalysis

Abstract: The main purpose of steganography is to hide the occurrence of communication. While most methods in use today are invisible to an observer's senses, mathematical analysis may reveal statistical anomalies in the stego medium. These discrepancies expose the fact that hidden communication is happening. This paper presents improved methods for information hiding. One method uses probabilistic embedding to minimize modifications to the cover medium. Another method employs error-correcting codes, which allow the embedding process to choose which bits to modify in a way that decreases the likelihood of being detected. In addition, we can hide multiple data sets in the same cover medium to provide plausible deniability. To prevent detection by statistical tests, we preserve the statistical properties of the cover medium. After applying a correcting transform to an image, statistical steganalysis is no longer able to detect the presence of steganography. We present an a priori estimate to determine the amount of data that can be hidden in the image while still being able to maintain frequency count based statistics. This way, we can quickly choose an image in which a message of a given size can be hidden safely. To evaluate the effectiveness of our approach, we present statistical tests for the JPEG image format and explain how our new method defeats them.

A robust image authentication method distinguishing JPEG compression from malicious manipulation

Abstract: Image authentication verifies the originality of an image by detecting malicious manipulations. Its goal is different from that of image watermarking, which embeds into the image a signature surviving most manipulations. Most existing methods for image authentication treat all types of manipulation equally (i.e., as unacceptable). However, some practical applications demand techniques that can distinguish acceptable manipulations (e.g., compression) from malicious ones. In this paper, we present an effective technique for image authentication which can prevent malicious manipulations but allow JPEG lossy compression. The authentication signature is based on the invariance of the relationships between discrete cosine transform (DCT) coefficients at the same position in separate blocks of an image. These relationships are preserved when DCT coefficients are quantized in JPEG compression. Our proposed method can distinguish malicious manipulations from JPEG lossy compression regardless of the compression ratio or the number of compression iterations. We describe adaptive methods with probabilistic guarantee to handle distortions introduced by various acceptable manipulations such as integer rounding, image filtering, image enhancement, or scaling-recaling. We also present theoretical and experimental results to demonstrate the effectiveness of the technique.

A feature-based algorithm for detecting and classifying scene breaks

Abstract: We describe a new approach to the detection and classification of scene breaks in video sequences. Our method can detect and classify a variety of scene breaks, including cuts, fades, dissolves and wipes, even in sequences involving significant motion. We detect the appearance of intensity edges that are distant from edges in the previous frame. A global motion computation is used to handle camera or object motion. The algorithms we propose withstand compression artifacts such as those introduced by JPEG and MPEG, even at very high compression rates. Experimental evidence demonstrates that our method can detect and classify scene breaks that are difficult to detect with previous approaches. An initial implementation runs at approximately 2 frames per second on a Sun workstation.