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.

Apparatus and method for a generalized benford's law analysis of DCT and JPEG coefficients

Abstract: A method and apparatus for a novel statistical model based on Benford's law for the probability distributions of the first digits of the block-DCT and quantized JPEG coefficients. A parametric logarithmic law, the generalized Benford's law, is formulated. Furthermore, some potential applications of this model in image forensics, which include the detection of JPEG compression for images in bitmap format, the estimation of JPEG compression Q-factor for JPEG compressed bitmap image, and the detection of double compressed JPEG image. Experimental results demonstrate the effectiveness of the statistical model used in embodiments of the invention.

Compressed pattern matching in jpeg images

Abstract: The possibility of applying compressed matching in JPEG encoded images is investigated and the problems raised by the scheme are discussed. A part of the problems can be solved by the use of some auxiliary data which yields various time/space trade-offs. Finally, approaches to deal with extensions such as allowing scaling or rotations are suggested.

Chaotic watermarking scheme for authentication of JPEG Images

Abstract: -With developing of computer networks and digital techniques, the electronic image are easily created, edited, reproduced and distributed. Unfortunately, illegal copy and malicious tamper are also facilitated. At present, fragile watermark is researched greatly to authenticate the veracity and integrity of electronic contents. In this paper, a chaotic watermarking scheme for authentication of popular JPEG images is proposed. The quantized DCT ( Discrete Cosine Transform ) coefficients after entropy decoding are mapped to the initial values of the chaotic system, then the generated watermark information by chaotic iteration is embedded into JPEG compressed domain. Thanks to the high sensitivity on initial values of the chaotic mapping, the very accurate localization is realized for the malicious tampers to JPEG images. Because we directly modify the DCT coefficients after quantization for embedding the watermark, the proposed method can prevent the invalidation of tamper detection by JPEG re-quantization. Furthermore, because the proposed scheme avoids a large of computation on full decoding and re-encoding process, the low complexity and a high extracting speed are obtained. Simulation results show the proposed scheme can directly localize the tampers happened on the watermarked JPEG images. Furthermore, the ability of tamper localization is very sensitivity. So the proposed scheme is very fit for the integrity authentication of the electronic image in Internet.

Three-dimensional transform coding of multispectral data

Abstract: We present a three-dimensional terrain-adaptive transform-based bandwidth compression technique for multispectral imagery. The transformation involves one dimensional Karhunen-Loeve transform (KLT) followed by two-dimensional discrete cosine transform. The algorithm exploits the inherent spectral and spatial correlations in the data. The images are spectrally decorrelated via the KLT to produce the eigen images. The resulting spectrally-decorrelated eigen images are then compressed using the JPEG algorithm. The algorithm is conveniently parameterized to accommodate reconstructed image fidelities ranging from near-lossless at about 5:1 compression ratio (CR) to visually lossy beginning at around 40:1 CR. A significant practical advantage of this approach is that it is leveraged on the standard and highly developed JPEG compression technology. Because of the significant compaction of the data resulting from the initial KLT process, an 8-bit JPEG can be used for coding the eigen images associated with 8, 10, or 12 bits multispectral data. The novelty of this technique lies in its unique capability to adaptively vary the characteristics of the spectral decorrelation transformation based upon the local terrain variation. >

Evaluation and comparison of JPEG2000 and vector quantization based onboard data compression algorithm for hyperspectral imagery

Abstract: This paper evaluates and compares JPEG 2000 and Successive Approximation Multi-stage Vector Quantization (SAMVQ) compression algorithms for hyperspectral imagery. PSNR was used to measure the statistical performance of the two compression algorithms. The SAMVQ outperforms JPEG 2000 by 17 dB of PSNR at the same compression ratios. The preservation of both spatial and spectral features was evaluated qualitatively and quantitatively. The SAMVQ outperforms JPEG 2000 in both spatial and spectral features preservation.