Showing papers on "JPEG published in 1999"

Hidden digital watermarks in images

Abstract: An image authentication technique by embedding digital "watermarks" into images is proposed. Watermarking is a technique for labeling digital pictures by hiding secret information into the images. Sophisticated watermark embedding is a potential method to discourage unauthorized copying or attest the origin of the images. In our approach, we embed the watermarks with visually recognizable patterns into the images by selectively modifying the middle-frequency parts of the image. Several variations of the proposed method are addressed. The experimental results show that the proposed technique successfully survives image processing operations, image cropping, and the Joint Photographic Experts Group (JPEG) lossy compression.

Digital watermarking for telltale tamper proofing and authentication

Abstract: In this paper, we consider the problem of digital watermarking to ensure the credibility of multimedia. We specifically address the problem of fragile digital watermarking for the tamper proofing of still images. Applications of our problem include authentication for courtroom evidence, insurance claims, and journalistic photography. We present a novel fragile watermarking approach which embeds a watermark in the discrete wavelet domain of the image by quantizing the corresponding coefficients. Tamper detection is possible in localized spatial and frequency regions. Unlike previously proposed techniques, this novel approach provides information on specific frequencies of the image that have been modified. This allows the user to make application-dependent decisions concerning whether an image, which is JPEG compressed for instance, still has credibility. Analysis is provided to evaluate the performance of the technique to varying system parameters. In addition, we compare the performance of the proposed method to existing fragile watermarking techniques to demonstrate the success and potential of the method for practical multimedia tamper proofing and authentication.

A feature-based algorithm for detecting and classifying production effects

Abstract: We describe a new approach to the detection and classification of production effects in video sequences. Our method can detect and classify a variety of effects, including cuts, fades, dissolves, wipes and captions, 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 algorithm we propose withstands JPEG and MPEG artifacts, even at high compression rates. Experimental evidence demonstrates that our method can detect and classify production effects that are difficult to detect with previous approaches.

Images with self-correcting capabilities

Abstract: In this paper, we introduce two techniques for self-embedding an image in itself as a means for protecting the image content. After self-embedding, it is possible to recover portions of the image that have been cropped out, replaced, damaged, or otherwise tampered without accessing the original image. The first method is based on transforming small 8/spl times/8 blocks using a DCT, quantizing the coefficients, and carefully encoding them in the least significant bits of other, distant squares. This method provides very high quality of reconstruction but it is very fragile. The quality of the reconstructed image areas is roughly equivalent to a 50% quality JPEG compressed original. The second method uses a principle similar to differential encoding to embed a circular shift of the original image with decreased color depth into the original image. The quality of the reconstructed image gradually degrades with increasing amount of noise in the tampered image. The first technique can also be used as a fragile watermark for image authentication, while the second technique can be classified as a semi-robust watermark.

Blur determination in the compressed domain using DCT information

Abstract: The paper presents a simple yet robust measure of image quality in terms of global (camera) blur. It is based on histogram computation of non-zero DCT coefficients. The technique is directly applicable to images and video frames in compressed (MPEG or JPEG) domain and to all types of MPEG frames (I-, P- or B-frames). The resulting quality measure is proved to be in concordance with subjective testing and is therefore suitable for quick qualitative characterization of images and video frames.

Adaptive motion-vector resampling for compressed video downscaling

Abstract: Digital video is becoming widely available in compressed form, such as a motion JPEG or MPEG coded bitstream. In applications such as video browsing or picture-in-picture, or in transcoding for a lower bit rate, there is a need to downscale the video prior to its transmission. In such instances, the conventional approach to generating a downscaled video bitstream at the video server would be to first decompress the video, perform the downscaling operation in the pixel domain, and then recompress it as, say, an MPEG, bitstream for efficient delivery. This process is computationally expensive due to the motion-estimation process needed during the recompression phase. We propose an alternative compressed domain-based approach that computes motion vectors for the downscaled (N/2xN/2) video sequence directly from the original motion vectors for the N/spl times/N video sequence. We further discover that the scheme produces better results by weighting the original motion vectors adaptively. The proposed approach can lead to significant computational savings compared to the conventional spatial (pixel) domain approach. The proposed approach is useful for video severs that provide quality of service in real time for heterogeneous clients.

Compressed image file formats: JPEG, PNG, GIF, XBM, BMP

Abstract: Preface. Acknowledgments. 1. Introduction. The Representation of Images. Vector and Bitmap Graphics. Color Models. True Color versus Palette. Compression. Byte and Bit Ordering. Color Quantization. A Common Image Format. Conclusion. 2. Windows BMP. Data Ordering. File Structure. Compression. Conclusion. 3. XBM. File Format. Reading and Writing XBM Files. Conclusion. 4. Introduction to JPEG. JPEG Compression Modes. What Part of JPEG Will Be Covered in This Book? What are JPEG Files? SPIFF File Format. Byte Ordering. Sampling Frequency. JPEG Operation. Interleaved and Noninterleaved Scans. Conclusion. 5. JPEG File Format. Markers. Compressed Data. Marker Types. JFIF Format. Conclusion. 6. JPEG Human Coding. Usage Frequencies. Huffman Coding Example. Huffman Coding Using Code Lengths. Huffman Coding in JPEG. Limiting Code Lengths. Decoding Huffman Codes. Conclusion. 7. The Discrete Cosine Transform. DCT in One Dimension. DCT in Two Dimensions. Basic Matrix Operations. Using the 2-D Forward DCT. Quantization. Zigzag Ordering. Conclusion. 8. Decoding Sequential-Mode JPEG Images. MCU Dimensions. Decoding Data Units. Decoding Example. Processing DCT Coefficients. Up-Sampling. Restart Marker Processing. Overview of JPEG Decoding. Conclusion. 9. Creating Sequential JPEG Files. Compression Parameters. Output File Structure. Doing the Encoding. Down-Sampling. Interleaving. Data Unit Encoding. Huffman Table Generation. Conclusion. 10. Optimizing the DCT. Factoring the DCT Matrix. Scaled Integer Arithmetic. Merging Quantization and the DCT. Conclusion. 11. Progressive JPEG. Component Division in Progressive JPEG. Processing Progressive JPEG Files. Processing Progressive Scans. MCUs in Progressive Scans. Huffman Tables in Progressive Scans. Data Unit Decoding. Preparing to Create Progressive JPEG Files. Encoding Progressive Scans. Huffman Coding. Data Unit Encoding. Conclusion. 12. GIF. Byte Ordering. File Structure. Interlacing. Compressed Data Format. Animated GIF. Legal Problems. Uncompressed GIF. Conclusion. 13. PNG. History. Byte Ordering. File Format. File Organization. Color Representation in PNG. Device-Independent Color. Gamma. Interlacing. Critical Chunks. Noncritical Chunks. Conclusion. 14. Decompressing PNG Image Data. Decompressing the Image Data. Huffman Coding in Deflate. Compressed Data Format. Compressed Data Blocks. Writing the Decompressed Data to the Image. Conclusion. 15. Creating PNG Files. Overview. Deflate Compression Process. Huffman Table Generation. Filtering. Conclusion. Glossary. Bibliography. Index. 0201604434T04062001

Image compression with neural networks } A survey

Abstract: Apart from the existing technology on image compression represented by series of JPEG, MPEG and H.26x standards, new technology such as neural networks and genetic algorithms are being developed to explore the future of image coding. Successful applications of neural networks to vector quantization have now become well established, and other aspects of neural network involvement in this area are stepping up to play significant roles in assisting with those traditional technologies. This paper presents an extensive survey on the development of neural networks for image compression which covers three categories: direct image compression by neural networks; neural network implementation of existing techniques, and neural network based technology which provide improvement over traditional algorithms.

Reduction of blocking artifacts in image and video coding

Abstract: The discrete cosine transform (DCT) is the most popular transform for image and video compression. Many international standards such as JPEG, MPEG, and H.261 are based on a block-DCT scheme. High compression ratios are obtained by discarding information about DCT coefficients that is considered to be less important. The major drawback is visible discontinuities along block boundaries, commonly referred to as blocking artifacts. These often limit the maximum compression ratios that can be achieved. Various postprocessing techniques have been published that reduce these blocking effects, but most of them introduce unnecessary blurring, ringing, or other artifacts. In this paper, a novel postprocessing algorithm based on Markov random fields (MRFs) is proposed. It efficiently removes blocking effects while retaining the sharpness of the image and without introducing new artifacts. The degraded image is first segmented into regions, and then each region is enhanced separately to prevent blurring of dominant edges. A novel texture detector allows the segmentation of images containing both texture and monotone areas. It finds all texture regions in the image before the remaining monotone areas are segmented by an MRF segmentation algorithm that has a new edge component incorporated to detect dominant edges more reliably. The proposed enhancement stage then finds the maximum a posteriori estimate of the unknown original image, which is modeled by an MRF and is therefore Gibbs distributed. A very efficient implementation is presented. Experiments demonstrate that our proposed postprocessor gives excellent results compared to other approaches, from both a subjective and an objective viewpoint. Furthermore, it will be shown that our technique also works for wavelet encoded images, which typically contain ringing artifacts.

Geometric-structure-based error concealment with novel applications in block-based low-bit-rate coding

Abstract: This paper first proposes a computationally efficient spatial directional interpolation scheme, which makes use of the local geometric information extracted from the surrounding blocks. The proposed error-concealment scheme produces results that are superior to those of other approaches, in terms of both peak signal-to-noise ratio and visual quality. Then a novel approach that incorporates this directional spatial interpolation at the receiver is proposed for block-based low-bit-rate coding. The key observation is that the directional spatial interpolation at the receiver can reconstruct faithfully a large percentage of the blocks that are intentionally not sent. A rate-distortion optimal way to drop the blocks is shown. The new approach can be made compatible with standard JPEG and MPEG decoders. The block-dropping approach also has an important application for dynamic rate shaping in transmitting precompressed videos over channels of dynamic bandwidth. Experimental results show that the proposed coding and rate-shaping systems can provide significant subjective and objective gains over conventional approaches.

Digital Image Compression Techniques

Abstract: This chapter describes digital image compression techniques, and the JPEG image compression standard. Digital image compression techniques are based on algorithms such as the Wavelet transform, Fractal images, Vector Quantisation and Discrete Cosine Transform (DCT). The digital image compression technique developed by the Joint Photographic Experts Group (JPEG) is mainly based on the quantisation of the DCT.

Requantization for transcoding of MPEG-2 intraframes

Abstract: An investigation on requantization for transcoding of video signals is carried out. Specifically, MPEG-2 compatible discrete cosine transform (DCT) intraframe coding is addressed. The aim of this work is twofold: first, to provide a theoretical analysis of the transcoding problem, and second, to derive quantization methods for efficient transcoding based on the results of the analysis. The mean squared error (MSE) cost function is proposed for designing a quantizer with minimum distortion resulting in up to 1.3 dB gain compared with the quantizer used in the MPEG-2 reference coder TM5. However, the MSE quantizer leads in general to a larger bit rate and may therefore only be applied locally to blocks of sensitive image content. A better rate-distortion performance can be provided by the maximum a posteriori (MAP) cost function. In critical cases, the MAP quantizer gives a 0.4 dB larger signal-to-noise-ratio (SNR) at the same bit rate compared with the TM5 quantizer. The results are not limited to MPEG-2 and can be adapted to other coding schemes such as H.263 or JPEG.

Issues and solutions for authenticating MPEG video

Abstract: Video authentication techniques are used to prove the originality of received video content and to detect malicious tampering. Existing authentication techniques protect every single bit of the video content and do not allow any form of manipulation. In real applications, this may not be practical. In several situations, compressed videos need to be further processed to accommodate various application requirements. Examples include bitrate scaling, transcoding, and frame rate conversion. The concept of asking each intermediate processing stage to add authentication codes is flawed in practical cases. In this paper, we extend our prior work on JPEG- surviving image authentication techniques to video. We first discuss issues of authenticating MPEG videos under various transcoding situations, including dynamic rate shaping, requantization, frame type conversion, and re-encoding. Different situations pose different technical challenges in developing robust authentication techniques. In the second part of this paper, we propose a robust video authentication system which accepts some MPEG transcoding processes but is able to detect malicious manipulations. It is based on unique invariant properties of the transcoding processes. Digital signature techniques as well as public key methods are used in our robust video authentication system.

JPEG compression metric as a quality-aware image transcoding

Abstract: Transcoding is becoming a preferred technique to tailor multimedia objects for delivery across variable network bandwidth and for storage and display on the destination device. This paper presents techniques to quantify the quality-versus-size tradeoff characteristics for transcoding JPEG images. We analyze the characteristics of images available in typical Web sites and explore how we can perform informed transcoding using the JPEG compression metric. We present the effects of this transcoding on the image storage size and image information quality. We also present ways of predicting the computational cost as well as potential space benefits achieved by the transcoding. These results are useful in any system that uses transcoding to reduce access latencies, increase effective storage space as well as reduce access costs.

Wavelet based watermarking method for digital images using the human visual system

Abstract: A wavelet based multiresolution watermarking method using the human visual system (HVS) is proposed, with the number of watermarks embedded proportional to the energy contained in each band. Experiments show that the proposed three-level wavelet based watermarking method is robust to some attacks such as, for example, joint photographic experts group (JPEG) compression, smoothing and cropping, collusion.

Image transformations in the compressed domain

Abstract: Image processing techniques which involve direct manipulation of the compressed domain representation of an image to achieve the desired spatial domain processing without having to go through a complete decompression and compression process. The techniques include processing approaches for performing the eight operations in D4 (the dihedral group of symmetries of a square) on JPEG images using the discrete cosine transform (DCT) domain representation of the images directly. For a task such as image rotation by 90° (an operation in D4), DCT-domain based methods can yield nearly a five-fold increase in speed over a spatial-domain based technique. These simple compressed-domain based processing techniques are well suited to the imaging tasks that are needed in a JPEG-based digital still-camera system.

Scalable wavelet coding for synthetic/natural hybrid images

Abstract: This paper describes the texture representation scheme adopted for MPEG-4 synthetic/natural hybrid coding (SNHC) of texture maps and images. The scheme is based on the concept of multiscale zerotree wavelet entropy (MZTE) coding technique, which provides many levels of scalability layers in terms of either spatial resolutions or picture quality, MZTE, with three different modes (single-Q, multi-Q, and bilevel), provides much improved compression efficiency and fine-gradual scalabilities, which are ideal for hybrid coding of texture maps and natural images. The MZTE scheme is adopted as the baseline technique for the visual texture coding profile in both the MPEG-4 video group and SNHC group. The test results are presented in comparison with those coded by the baseline JPEG scheme for different types of input images, MZTE was also rated as one of the top five schemes in terms of compression efficiency in the JPEG2000 November 1997 evaluation, among 27 submitted proposals.

Prolog to - High-performance compression of visual information-a tutorial review- part I: still pictures

Abstract: Digital images have become an important source of information in the modern world of communication systems. In their raw form, digital images require a tremendous amount of memory. Many research efforts have been devoted to the problem of image compression in the last two decades. Two different compression categories must be distinguished: lossless and lossy. Lossless compression is achieved if no distortion is introduced in the coded image. Applications requiring this type of compression include medical imaging and satellite photography. For applications such as video telephony or multimedia applications, some loss of information is usually tolerated in exchange for a high compression ratio. In this two-part paper, the major building blocks of image coding schemes are overviewed. Part I covers still image coding, and Part II covers motion picture sequences. In this first part, still image coding schemes have been classified into predictive, block transform, and multiresolution approaches. Predictive methods are suited to lossless and low-compression applications. Transform-based coding schemes achieve higher compression ratios for lossy compression but suffer from blocking artifacts at high-compression ratios. Multiresolution approaches are suited for lossy as well for lossless compression. At lossy high-compression ratios, the typical artifact visible in the reconstructed images is the ringing effect. New applications in a multimedia environment drove the need for new functionalities of the image coding schemes. For that purpose, second-generation coding techniques segment the image into semantically meaningful pairs. Therefore, parts of these methods have been adapted to work for arbitrarily shaped regions. In order to add another functionality, such as progressive transmission of the information, specific quantization algorithms must he defined. A final step in the compression scheme is achieved by the codeword assignment. Finally, coding results are presented which compare state-of-the-art techniques for lossy and lossless compression. The different artifacts of each technique are highlighted and discussed. Also, the possibility of progressive transmission is illustrated.

Content-based integrity protection of digital images

Abstract: The increasing availability of digitally stored information and the development of new multimedia broadcasting services, has recently motivated research on copyright protection and authentication schemes for these services. Possible solutions range from low-level systems based upon header description associated with the bit-stream (labelling), up to high level, holographically inlayed, non-deletable systems (watermarking). This paper is focused on authentication, using the labeling approach; a generic framework is firstly presented and two specific methods are then proposed for the particular cases of still images and videos. The resistance of both methods to JPEG and MPEG2 compression, as well as its sensitivity to image manipulations, are evaluated.© (1999) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

Detection of Interest Points for Image Indexation

Abstract: This paper addresses the problem of detection and delineation of interest points in images as part of an automatic image and video indexing for search by content purposes project. We propose a novel key point detector based on multiresolution contrast information. We compare this detector to the Plessey feature point detector as well as the detector introduced in the SUSAN project. As we are interested in common database applications, we focus this comparison on robustness versus coding noise like Jpeg noise.

JPEG2000, the next millennium compression standard for still images

Abstract: With the increasing use of multimedia technologies, image compression requires higher performance as well as new functionality. To address this need in the specific area of still image encoding, a new standard is currently being designed: JPEG2000. We see what the exact goals are of this future standard, which applications it addresses and the current standardisation process. Then we show through the descriptions of two available demonstrations what kind of results are already reachable with the current status of the standard. The first demonstration describes a Java implementation of the future standard, details the advantages of such an implementation and compares the performance of JPEG2000 with that of JPEG. The second demonstration describes how JPEG2000 can be used in domains were the transmission bandwidth is very restricted, taking advantages of new functions such as the definition of regions of interest and progressive transmission.

Postprocessing for very low bit-rate video compression

Abstract: This paper presents a novel postprocessing algorithm developed specifically for very low bit-rate MC-DCT video coders operating at low spatial resolution, postprocessing is intricate in this situation because the low sampling rate (as compared to the image feature size) makes it very easy to overfilter, producing excessive blurring. The proposed algorithm uses pixel-by-pixel processing to identify and reduce both blocking artifacts and mosquito noise while attempting to preserve the sharpness and naturalness of the reconstructed video signal and minimize the system complexity. Experimental results show that the algorithm successfully reduces artifacts in a 16 kb/s scene-adaptive coder for video signals sampled at 80/spl times/112 pixels per frame and 5-10 frames/s. Furthermore, the portability of the proposed algorithm to other block-DCT based compression systems is shown by applying it, without modification, to successfully post-process a JPEG-compressed image.

Semi-fragile watermarks

Abstract: A method is presented for marking high-quality digital images with a robust and invisible watermark. It requires the mark to survive and remain detectable and authenticatable through all image manipulations that in themselves do not damage the image beyond useability. These manipulations include JPEG “lossy” compression and, in the extreme, the printing and rescanning of the image. The watermark also has the property that it can detect if the essential contents of the image has changed. The first phase of the method comprises extracting a digest or number N from the image so that N only (or mostly) depends on the essential information content, such that the same number N can be obtained from a scan of a high quality print of the image, from the compressed form of the image, or in general, from the image after minor modifications (introduced inadvertently by processing, noise etc.). The second phase comprises the marking. This can be done in form of an invisible robust watermark, or in form of some visible signature or watermark.

Digital watermarking of images and video using direct sequence spread spectrum techniques

Abstract: We analyze the spread spectrum technique of watermarking images and video. The technique can be used for both spatial and spectral domain watermarking. The watermarking procedure could be incorporated with the standard compression algorithm or could be performed on already available JPEG or MPEG streams after partial decoding. The spread spectrum method has the advantage that the watermark extraction is possible without using the original unmarked image. The simulation results show the robustness of the watermark to image degradations such as lossy compression as in JPEG and MPEG, spatial filtering, cropping, etc.

Biased reconstruction for JPEG decoding

Abstract: Assuming a Laplacian distribution, there exists a well known method for optimally biasing the reconstruction levels for the quantized ac discrete cosine transform (DCT) coefficients in the JPEG decoder. This, however, requires an estimate of the Laplacian distribution parameter. We derive a new, maximum likelihood estimate of the Laplacian parameter using only the quantized coefficients available at the decoder. We quantify the benefits of biased reconstruction through extensive simulations and demonstrate that such improvements are very close to the best possible resulting from centroid reconstruction.

A robust data hiding scheme for images using DFT

Abstract: We present a data hiding scheme for still images, in which only the magnitude of the DFT coefficients are altered to embed the hidden information bits. We begin by identifying various components of a typical data hiding scheme, like the decomposition used, signature design, self-noise suppression and signaling. The final choice of components for the proposed data hiding scheme are well tailored by utilizing theoretical reasonings and experimental observations. Performance results show good robustness of the data hiding scheme for both JPEG and SPIHT image compression.

Optimal blockwise dependent quantization for stereo image coding

Abstract: Research in coding of stereo images has focused mostly on the issue of disparity estimation to exploit the redundancy between the two images in a stereo pair, with less attention being devoted to the equally important problem of allocating bits between the two images. This bit allocation problem is complicated by the dependencies arising from using a prediction based on the quantized reference images. We address the problem of blockwise bit allocation for coding of stereo images and show how, given the special characteristics of the disparity field, one can achieve an optimal solution with reasonable complexity, whereas in similar problems in motion compensated video only approximate solutions are feasible. We present algorithms based on dynamic programming that provide the optimal blockwise bit allocation. Our experiments based on a modified JPEG coder show that the proposed scheme achieves higher mean peak signal-to-noise ratio over the two frames (0.2-0.5 dB improvements) as compared with blockwise independent quantization. We also propose a fast algorithm that provides most of the gain at a fraction of the complexity.

From LOGO-I to the JPEG-LS standard

Abstract: LOGO-I (LOw COmplexity LOssless COmpression for Images) is the algorithm at the core of the new ISO/ITU standard for lossless and near-lossless compression of continuous-tone images, JPEG-LS. The algorithm was conceived as a "low complexity projection" of the universal context modeling paradigm, matching its modeling unit to a simple coding unit based on Golomb codes. The JPEG-LS standard evolved after successive refinements of the core algorithm, and a description of its design principles and main algorithmic components is presented in this paper. LOCO-I/JPEG-LS attains compression ratios similar or superior to those obtained with state-of-the-art schemes based on arithmetic coding. Moreover, it is within a few percentage points of the best available compression ratios, at a much lower complexity level.

High quality face recognition in JPEG compressed images

Abstract: This paper presents an advanced face recognition system that is based on the use of Pseudo 2-D HMMs and coefficients of the 2-D DCT as features. A major advantage of our approach is the fact that our face recognition system works directly with JPEG-compressed face images, i.e. it uses directly the DCT-features provided by the JPEG standard, without any necessity of completely decompressing the image before recognition. The recognition rates on the Olivetti Research Laboratory (ORL) face database are 100% for the original images and 99.5% for JPEG compressed domain recognition. A comparison with other face recognition systems evaluated on the ORL database, shows that these are the best recognition results on this database.