nils-herrmann/clean_scirepeval huggingface dataset:
Format-Independent Authentication of Arbitrary Scalable Bit-Streams using One-Way Accumulators

We propose a mechanism for authentication of general scalable bit-streams, based on quasi-commutative one-way accumulator functions. Such functions allow flexible partitioning between an auxiliary hash computed for removed parts of an original bit-stream and the hash that a receiver can compute from the received bit-stream, and yet allow generation of a common root hash for the original bit-stream against which the authentication may be conducted. Unlike prior work using Merkle hash trees, the number of auxiliary hashes to be transmitted is always one, independent of the actual version of the bit-stream to be authenticated, and the mechanism is independent of the order of hash accumulation. Further, the method readily lends itself to format-independent authentication and adaptation mechanism by use of appropriate standardized metadata.
Combined mode selection and macroblock quantization step adaptation for the H.263 video encoder

The low bitrate video coding standard H.263 allows four modes of coding, and 31 quantization parameters for each macroblock in a sequence. A new quantization parameter can be set at the beginning of each group of blocks (GOB), and then adapted from macroblock to macroblock within the GOB in a constrained manner. In this work, for every GOB in a frame, an m-best search scheme is employed through a trellis to find the best modes and the best quantizer step changes, in a rate-distortion sense, for both when the starting quantization parameter is predetermined, and when it is to be selected optimally as well. Thus the algorithm performs the most generic kind of optimization at the macroblock level for the P-frames of H.263. It is demonstrated that a relatively low search depth is sufficient to produce coding results superior to established standard-compatible coders.
Video Description Length Guided Constant Quality Video Coding with Bitrate Constraint

In this paper, we propose a new video encoding strategy - Video description length guided Constant Quality video coding with Bitrate Constraint (V-CQBC), for large scale video transcoding systems of video charing websites with varying unknown video contents. It provides smooth quality and saves bitrate and computation for transcoding millions of videos in both real time and batch mode. The new encoding strategy is based on the average bitrate-quality regression model and adapt to the encoded videos. Furthermore, three types of video description length (VDL), describing the video overall, spatial and temporal content complexity, are proposed to guide video coding. Experimental results show that the proposed coding strategy with saved computation could achieve better or similar RD performance than other coding strategies.
PathMarker: systems for capturing trips

Central to capturing a trip is knowing where you were, and when you were there. Combining continuous path data with media (path-enhanced media or PEM) offers substantial advantages over the previous approach of tagging individual media with time and location. Prototype systems, collectively called PathMarker, are used for gathering, editing, presenting and browsing PEM. We have developed: (1) a methodology for gathering PEM with off-the-shelf hardware; (2) software for automatic conversion of the raw path data and media into an application independent XML representation; (3) two example PEM applications. The first application provides map-overlaid trip editing, presentation and browsing. The second application provides a 3D immersive environment with digital elevation maps for automatic trip flybys and for browsing. Experience with a number of recorded trips confirms that PathMarker systems seem to capture the essence of a trip.
Super resolution of video using key frames

In many video compression systems, the frames are down-sampled before transmission. Also, in many scalable systems, the residual after down- and up-sampling is encoded and transmitted. Sometimes, a few frames are encoded at normal resolution (key frames) while the other frames are encoded at reduced resolution. Super resolution can be used to enhance the up-sampling process, using motion information to improve traditional interpolation. In this paper, we propose to use a super resolution method to up-sample the non-key frames using the key frames as reference. We build dictionaries on-the- fly using the key frames instead of the traditional off-line training images. The high-frequency data of matching blocks are added to the low-resolution blocks. Since the key frames are very similar to the non-key frames, the method is robust enough to allow successful super resolution of highly compressed (severely degraded) sequences. Results are presented for many predefined block sizes, key frames frequencies, and compression parameters.
Distributed image coding for imformation recovery from the print-scan channel

A printed photograph is difficult to reuse because the digital pixels that generated it are no longer available. This paper describes approximating the original digital pixels by combining a scan of the printed photograph with small amounts of digital auxiliary information kept with the print, using an encoding such as a dense barcode. The auxiliary information enables accurate registration and color-reproduction, and the recovery of information lost due to the print-scan channel, by distributed source coding techniques. Approximating the original digital image enables many uses, including making high-fidelity reprints, as well as robust watermark detection. A block entropy coder using terminated tree codes for cosets of DCT coefficients is proposed for distributed image coding.
Optimal adaptation decision-taking for terminal and network quality-of-service

In order to cater to the diversity of terminals and networks, efficient, and flexible adaptation of multimedia content in the delivery path to end consumers is required. To this end, it is necessary to associate the content with metadata that provides the relationship between feasible adaptation choices and various media characteristics obtained as a function of these choices. Furthermore, adaptation is driven by specification of terminal, network, user preference or rights based constraints on media characteristics that are to be satisfied by the adaptation process. Using the metadata and the constraint specification, an adaptation engine can take an appropriate decision for adaptation, efficiently and flexibly. MPEG-21 Part 7 entitled Digital Item Adaptation standardizes among other things the metadata and constraint specifications that act as interfaces to the decision-taking component of an adaptation engine. This paper presents the concepts behind these tools in the standard, shows universal methods based on pattern search to process the information in the tools to make decisions, and presents some adaptation use cases where these tools can be used.
A source and channel coding approach to data hiding with application to hiding speech in video

Digital data hiding is a technology being developed for multimedia services, where non-trivial amounts of signature data is invisibly hidden inside a host data source by the owner before the latter is freely distributed. Only those authorized can recover the hidden data from the host, even after the latter has undergone standard transformations such as compression. We adopt a quantitative source and channel coding approach to hiding large amounts of compressible signature data inside the raw host. The signature data is source coded by vector quantization, and the indices are embedded in the host by perturbing it using orthogonal transform domain vector perturbations. The transform coefficients of the parent data are grouped into vectors, and the vectors are perturbed using noise-resilient channel codes derived from multidimensional lattices. The perturbations are constrained by a maximum allowable mean-squared error that can be introduced in the host. The generic approach is readily adapted to make retrieval possible even for applications where the original host is not available to the retriever. This scheme is applied to hiding speech in video. The host video is wavelet transformed frame by frame, and vectors of coefficients are perturbed using lattice channel codes to represent hidden vector quantized speech. The embedded video is subjected to H.263 compression before retrieving the hidden speech from it. The retrieved speech is intelligible even with large compression ratios of the host video.
A framework for fully format-independent adaptation of scalable bit streams

This paper presents a framework for modeling and adaptation of arbitrary scalable multimedia bit streams in a manner that is fully format agnostic ("universal transcoding"). It is entitled structured scalable metaformats (SSM), and is based on establishing a universal model for all scalable bit streams, which in turn allows a compact specification of the set of allowed adaptations, and also how the bit stream adaptation is performed. In order to enable format-agnostic adaptation, two elements are standardized: 1) metadata associated with a scalable bit stream conveying the parameters of its SSM model, and how it is to be manipulated to obtain various adapted versions, as well as information that allows making appropriate adaptation decisions using only the model parameters and 2) a specification of outbound network and terminal constraints, for real-time decisions based on both user preferences and network conditions. By interpreting the descriptions, a universal adaptation engine can adapt the content to suit the specified needs and preferences of recipients, without knowledge of the specifics of the content, its encoding and encryption. With universal adaptation, different adaptation infrastructures are no longer needed for different types of scalable media, eliminating the high costs of traditional transcoding. Many of the SSM concepts have been adopted into the MPEG-21 Part 7 standard entitled Digital Item Adaptation.
Vector set partitioning with classified successive refinement VQ for embedded wavelet image coding

Set Partitioning in Hierarchical Trees (SPIHT), proposed by Said and Pearlman [1996], is generally regarded as a very efficient wavelet-based still image compression scheme. The algorithm uses an efficient, joint scanning and bit-allocation mechanism for quantizing the scalar wavelet coefficients, and produces a perfectly embedded bitstream. This work extends set partitioning to scan vectors of wavelet coefficients, and uses successive refinement VQ techniques such as multistage and tree-structured VQ, to quantize several wavelet coefficients at once. The new scheme is named VSPIHT (Vector SPIHT). Coding results are presented to demonstrate that the vector-based approach (without arithmetic coding) surpasses the scalar counterpart (also without arithmetic coding), in the mean-squared-error sense, for most images at low bitrates. The superiority of the vector-based approach is more pronounced for images that are generally regarded as difficult to code (such as Barbara) because of a large amount of detail.
Arithmetic coded vector SPIHT with classified tree-multistage VQ for color image coding

A vector extension of the set partitioning in hierarchical trees (SPIHT) algorithm, named vector-SPIHT (VSPIHT), using trained classified successive refinement VQ, has recently been proposed. In this work, vector set-partitioning is applied to multispectral image compression, in particular to 24-bit color images. Since the individual spectral components are sufficiently correlated, VSPIHT can effectively exploit both the inter-component redundancy as well as the spatial redundancy within each subband of each component, to yield performance superior to separate scalar SPIHT coding of each component. Adaptive arithmetic coding of the first stage VQ index for each class, as well as the significance information, further improves the performance. Coding results demonstrate that the vector-based approach for color images significantly outperforms the scalar counterpart in the mean-squared-error sense.
A switchable loop-restoration with side-information framework for the emerging AV1 video codec

Image restoration schemes have traditionally been targeted only for use in a blind scenario, where the aim is to improve the quality of an image or video after it has suffered degradations in capture, processing, storage, coding or transmission, at a time when the undegraded source is no longer available. However, these schemes can also be adopted for compression, because any information that can be restored can be saved, thereby aiding compressibility. In this use case, the source is known at the time of compression, and the encoder can send additional side-information to the decoder with the compressed bit-stream to specify how the decoder is supposed to restore. In this paper, we describe three novel schemes that are applied in-loop to reconstructed frames after a conventional deblocking loop filter has been applied. These schemes are switchable within a frame per suitably sized tile. The specific schemes described are based on separable symmetric Wiener filters, dual self-guided filters with subspace projection, and domain transform recursive filters. Results with the new coding tool are presented on the emerging AV1 video codec on standard test sets, showing upwards of 2% bit-rate savings.
Joint inter-intra prediction based on mode-variant and edge-directed weighting approaches in video coding

Most modern video compression codecs, like VP9, HEVC and H.264, encode square or rectangular blocks either by inter prediction or intra prediction. A joint inter-intra predictor that combines motion compensation and intra extrapolation by two novel weighting schemes is proposed to improve compression quality. Prior work on joint prediction employs inter-intra weights that only rely on the pixel locations. As an enhancement, we design a weighting approach by also considering the angle of intra prediction, which is the actual direction that the intra prediction errors evolve. Moreover, our second approach, inspired by prior work on geometric-partition-based motion compensation, breaks the limitation of traditional quad-tree partition by jointly using different predictors that implies soft step weighting functions for new and existing objects co-occurring around irregular motion edges. The proposed joint prediction approaches deliver consistent coding gains, as shown by extensive experiments on the experimental branch of VP9, Google's open source video compression tool.
JPEG2000-matched MRC compression of compound documents

The mixed raster content (MRC) ITU document compression standard (T.44) specifies a multilayer decomposition model for compound documents into two contone image layers and a binary mask layer for independent compression. While T.44 does not recommend any procedure for decomposition, it does specify a set of allowable layer codecs to be used after decomposition. While T.44 only allows older standardized codecs such as JPEG/JBIG/G3/G4, higher compression could be achieved if newer contone and bi-level compression standards such as JPEG2000/JBIG2 were used instead. We present an MRC compound document codec using JPEG2000 as the image layer codec and a layer decomposition scheme matched to JPEG2000 for efficient compression. JBIG still codes the mask. Noise removal routines enable efficient coding of scanned documents along with electronic ones. Resolution scalable decoding features are also implemented. The segmentation mask, obtained from layer decomposition, serves to separate text and other features.
Subband DCT: definition, analysis, and applications

The discrete cosine transform (DCT) is well known for its highly efficient coding performance and is widely used in many image compression applications. However, in low bit rate coding, it produces undesirable block artifacts that are visually not pleasing. In addition, in many practical applications, faster computation and easier VLSI implementation of DCT coefficients are also important issues. The removal of the block artifacts and faster DCT computation are therefore of practical interest. In this paper, we investigate a modified DCT computation scheme, to be called the subband DCT (SB-DCT), that provides a simple, efficient solution to the reduction of the block artifacts while achieving faster computation. We have applied the new approach for the low bit rate coding and decoding of images. Simulation results on real images have verified the improved performance obtained using the proposed method over the standard JPEG method.
Compact dependent key generation methods for encryption-based subscription differentiation for scalable bit-streams

Subscription differentiation can be easily supported by deploying a scalable (prioritized) bit-stream and encrypting different parts of the bit-stream with various keys. Based on the subscription level, only the keys corresponding to the authorized part of the bit-stream are transmitted to the receiver. Since state-of-the-art scalable bit-streams offer a plethora of spatial, temporal and SNR resolutions, the number of keys to communicate for the various resolutions can be very large and variable. In this paper, two methods are proposed to significantly reduce the number of keys to be communicated by using dependent keys related by one-way functions. The first method is based on using separate one-way function chains for the keys for each scalability dimension. The second method allows simultaneous key progression along multiple dimensions by using special types of quasi-commutative one-way functions called one-way accumulators. The resultant one-way structure is named the accumulator mesh.
Tables for practical Wyner-Ziv coding of Laplacian sources

Many practical coding scenarios deal with sources with transform coefficients that are well modeled as Laplacians. For the Wyner-Ziv coding problem for such sources when correlated side-information is available at the decoder, the side-information is modeled as obtained by independent additive Laplacian or Gaussian innovation on the source. This paper deals with the optimal choice of encoding parameters for practical Wyner-Ziv coding in such scenarios, using the same quantizer family as in the regular codec to cover a range of rate-distortion trade-offs, given the variances of the source and innovation. Using our prior analysis of a general encoding model based on multi-level coset codes combining source and channel coding, we present comprehensive tables with optimal encoding parameters. These tables can be readily incorporated into a practical codec to read off the encoding parameters.
Complexity Control for Real-Time Video Coding

A methodology for complexity scalable video encoding and complexity control within the framework of the H.264/AVC video encoder is presented. To yield good rate-distortion performance under strict complexity/time constraints for instance in real-time communication, a framework for optimal complexity allocation at the macroblock level is necessary. We developed a macroblock level fast motion estimation based complexity scalable motion/mode search algorithm where the complexity is adapted jointly by parameters that determine the aggressiveness of an early stop criteria, the number of ordered modes searched, and the accuracy of motion estimation steps for the INTER modes. Next, these complexity parameters are adapted per macroblock based on a control loop to approximately satisfy an encoding frame rate target. The optimal manner of adapting the parameters is derived from prior training. Results using the developed scalable complexity H.264/AVC encoder demonstrate the benefit of adaptive complexity allocation over uniform complexity scaling.
Multi-resolution redundancy for error-resilient video transmission

In this paper we advocate a multi-resolution mechanism for redundant information generation and transmission with low overheads in bit-rate, in order to enable reliable video communication over challenging lossy networks with low latency. Our previous work entitled RECAP, transmitted a low resolution redundant version of a parent video stream, in order to achieve effective concealment of isolated and burst losses by clever multi-frame super-resolution processing at the decoder. A reference picture selection mechanism was used to transmit the low-resolution redundant video with high guarantee and stop drift in case of losses. In this work, we extend the framework to incorporate an additional distributed Wyner-Ziv coding layer on the low-resolution information to further correct errors, and consequently improve the error-concealed picture quality. The error-concealed super-resolved frame using the low-resolution information alone, now acts as side-information at the decoder to correct additional errors by decoding the Wyner-Ziv layer. Preliminary results are presented to demonstrate the efficacy of the proposed approach.
Variable block-size overlapped block motion compensation in the next generation open-source video codec

Traditional motion compensation is based on a simplistic assumption of a piecewise constant and pure translational motion field. Premised on the inefficiency of such block-copying-based algorithms in compressing real-life videos, this paper proposes overlapped block motion compensation for AV1, a next generation open-source video codec. Motions assigned to surrounding blocks will contribute to predicting a current block, via a well-defined overlapping scheme appropriately designed for advanced variable block-size partitioning frameworks. To efficiently incorporate the proposed tool, the encoder is optimized with proper early termination to manage complexity in conjunction with weighted motion search accounting for non-uniformly weighted distortion in overlapped prediction. Moreover as an extension, by re-arranging decoding operations, we enable non-causal overlapping which also utilizes motions of bottom and right neighbors. Being verified by integration in the AV1 codec, the tools achieve considerable coding gains on various test sets.
Learning separable transforms by inverse covariance estimation

Orthogonal transforms are one of the most important components of a video encoder system. They are applied to residual block images obtained as the difference between a target and its prediction. In this paper we propose a framework to design separable transforms from prediction residual statistics. We model the data as a 2D Gaussian Markov random field and approximate its inverse covariance by a matrix with a separable structure, thus explicitly constructing a separable orthonormal matrix that approximates the KLT. Our designed transforms can adapt to prediction residual statistics, have low complexity (compared to non separable transforms), require selecting few parameters and outperform hybrid DCT/ADST separable transform for intra coding of AV1 residuals.
Linear-translate constrained storage VQ for VSPIHT wavelet image compression

A new constrained storage VQ (CSVQ) structure based on linear transforms and translates of a common root codebook is proposed. The new VQ structure, named LT-CSVQ (linear translate CSVQ) acts as a building block for multistage VQ implementations (LT-CS-MSVQ), and significantly reduces storage requirements from that required in tree-multistage VQ implementations. LT-CS-MSVQ is most appropriate for medium rate multistage VQ implementations, and is applied to the previously proposed vector enhancement of Said and Pearlman's (1996) set partitioning in hierarchical trees (SPIHT) image coder named VSPIHT.