Compressed Bit Research Articles

New rate-distortion modeling and efficient rate control for H.264/AVC video coding

Rate control (RC) is crucial in controlling compression bit rates and qualities for networked video applications. In this paper, we propose a new rate-distortion (R-D) model and an efficient rate control scheme for H.264/AVC video coding, which elegantly resolve the inter-dependency problem between rate-distortion optimization and rate control by eliminating the need of coding complexity prediction for an inter-frame. The objective is to achieve accurate bit rate, obtain optimal video quality while reducing quality variations and simultaneously handling buffer fullness effectively. The proposed algorithm encapsulates a number of new features, including a coding complexity measure for intra-frames, a rate-distortion model, an accurate quantization parameter (QP) estimation for intra-frames, an incremental quantization parameter calculation method for inter-frames, a proportional+integral+derivative (PID) buffer controller, and an intelligent bit-allocation-balancing technique. Our experimental results demonstrate that the proposed scheme outperforms the JVT-G012 solution by providing accurate rate regulation, effectively reducing frame skipping, and finally improving coding quality by up to 1.80 dB.

Compressed Binary Bit Trees: A New Data Structure For Accelerating Database Searching

Molecules are often represented as bit string fingerprints in databases. These bit strings are used for similarity searching using the Tanimoto coefficient and rapid indexing. A new data structure is introduced, the compressed bit binary tree, that rapidly increases search and indexing times by up to a factor of 30. Results will be shown for databases of up to 1 M compounds with a variety of search parameters.

Fast Fine Granularity Scalability Decoding Scheme for Low-Delay Scalable Video Coding Applications

The Fine Grain Scalability (FGS) technique used in SVC codec encodes and decodes the quantization error of QBL (quality base layer) along the cyclic scanning path. The FGS technique provides the scalability property to the compressed bit stream. However, the cyclic scanning procedure of FGS method may require a huge computing time. In this paper, we propose a fast FGS decoding scheme, which has a lower decoding complexity without sacrificing image quality.

Joint coding and embedding techniques for multimedia images

Hiding data in digital images is a technique for secret data communication. It involves embedding important data into a cover image in digital form with minimal perceptible degradation. In this paper, we first propose an improved data hiding method for side-match vector quantization (SMVQ) compressed images, which utilizes the codeword-pairing procedure to modulate the index code of each image block. In order to take it a step further and obtain a larger embedding capacity, we remodel the first proposed method into a new one with the power of variable-rate data embedding through the use of a multiple-base notational system. According to the experimental results, the two proposed methods are indeed capable of providing a larger embedding capacity without causing noticeable distortions of stego-images in comparison with previous methods. Moreover, our methods also maintain a low compression bit-rate without auxiliary data.

A compressed-domain approach for shot boundary detection on H.264/AVC bit streams

The amount of digital video content has grown extensively during recent years, resulting in a rising need for the development of systems for automatic indexing, summarization, and semantic analysis. A prerequisite for video content analysis is the ability to discover the temporal structure of a video sequence. In this paper, a novel shot boundary detection technique is introduced that operates completely in the compressed domain using the H.264/AVC video standard. As this specification contains a number of new coding tools, the characteristics of a compressed bit stream are different from prior video specifications. Furthermore, the H.264/AVC specification introduces new coding structures such as hierarchical coding patterns, which can have a major influence on video analysis algorithms. First, a shot boundary detection algorithm is proposed which can be used to segment H.264/AVC bit streams based on temporal dependencies and spatial dissimilarities. This algorithm is further enhanced to exploit hierarchical coding patterns. As these sequences are characterized by a pyramidal structure, only a subset of frames needs to be considered during analysis, allowing the reduction of the computational complexity. Besides the increased efficiency, experimental results also show that the proposed shot boundary detection algorithm achieves a high accuracy.

Compression-watermarking scheme for MPEG-4 fine granularity scalability video recompression and authentication

A novel fragile watermarking scheme is proposed. This scheme not only can verify the authenticity and integrity of the video streams with fine granularity scalability, but also can reduce the size of bit streams after embedding fragile watermark information into the base-layer stream and the bit-plane coding symbol in the enhancement-layer stream. For clarifying the effectiveness of the proposed scheme, a series of experimental simulations were conducted. The results show that the scheme can detect tampering modification in the content of video streams and identify the locations at which these modifications have been made. Furthermore, the scheme can further reduce the average length of the compressed bit stream by about 12%.

Redundant Slice Optimal Allocation for H.264 Multiple Description Coding

In this paper, a novel H.264 multiple description technique is proposed. The coding approach is based on the redundant slice representation option, defined in the H.264 standard. In presence of losses, the redundant representation can be used to replace missing portions of the compressed bit stream, thus yielding a certain degree of error resilience. This paper addresses the creation of two balanced descriptions based on the concept of redundant slices, while keeping full compatibility with the H.264 standard syntax and decoding behavior in case of single description reception. When two descriptions are available still a standard H.264 decoder can be used, given a simple preprocessing of the received compressed bit streams. An analytical setup is employed in order to optimally select the amount of redundancy to be inserted in each frame, taking into account both the transmission condition and the video decoder error propagation. Experimental results demonstrate that the proposed technique favorably compares with other H.264 multiple description approaches.

Video steganalysis based on aliasing detection

A novel steganalysis approach is proposed against additive video steganography. Under the assumption of independence between the cover video and hidden data, the probability mass function of the frame difference signal of stego-video generally reveals the aliasing effect caused by embedding data. The proposed method successfully detects the hidden data in video with different compression bitrates by detecting the aliasing degree.

Video compression by bit‐plane watermarking

AbstractThis article proposes a new fragile watermarking scheme named bit‐plane watermarking (BPW) which considers ways to improve coding efficiency whereas providing watermarking capability. Because of the use of the run‐length coding strategy for embedding watermark information, the BPW not only verifies the authenticity and integrity of video streams, but also can recompress the bit streams for improving the compression ratio. To verify the effectiveness of this new concept, we select the MPEG‐4 FGS as the platform for implementation. The watermark is embedded in the bit‐plane blocks of MPEG‐4 FGS enhancement layer bitstream, and the coefficient in each bit‐plane block is automatically selected so that the run‐length symbols can be reduced and the location of embedded bits is not required to memorize. The effectiveness of the proposed scheme is demonstrated in a series of experimental simulations. It is shown that the scheme successfully detects changes made to the content of MPEG‐4 FGS video streams and identifies the specific location at which these changes have been made. Furthermore, the results show that the scheme can further reduce the length of compressed bit stream. © 2008 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 18, 257–264, 2008; Published online in Wiley InterScience (www.interscience.wiley.com).

A CMOS Imager With Focal Plane Compression Using Predictive Coding

This paper presents a CMOS image sensor with focal-plane compression. The design has a column-level architecture and it is based on predictive coding techniques for image decorrelation. The prediction operations are performed in the analog domain to avoid quantization noise and to decrease the area complexity of the circuit. The prediction residuals are quantized and encoded by a joint quantizer/coder circuit. To save area resources, the joint quantizer/coder circuit exploits common circuitry between a single-slope analog-to-digital converter (ADC) and a Golomb-Rice entropy coder. This combination of ADC and encoder allows the integration of the entropy coder at the column level. A prototype chip was fabricated in a 0.35 mum CMOS process. The output of the chip is a compressed bit stream. The test chip occupies a silicon area of 2.60 mm times 5.96 mm which includes an 80 times 44 APS array. Tests of the fabricated chip demonstrate the validity of the design.

Novel Distortion Estimation Technique for Hardware-Based JPEG2000 Encoder System

Optimal rate-control is an important feature of JPEG2000 which allows simple truncation of compressed bit stream to achieve best image quality at a given target bit rate. Accurate distortion estimation (DE) with respect to the allowed bit stream truncation points, is essential for the rate-control performance. In this paper, we address the issues involved in accurate DE for the hardware oriented implementation of JPEG2000 encoding systems. We propose a novel hardware efficient DE technique. Rate control based on the proposed technique results in a average peak signal-to-noise ratio degradation of only 0.02 dB with respect to the optimal DE technique used in the software implementations of JPEG2000. This is the best performance reported in comparison to existing techniques. The proposed technique requires only an additional 4096 memory bits per block coder which is 80% less than the memory requirements of optimal technique.

Unidirectional Distributed Video Coding for Low Cost Video Encoding

Distributed video coding (DVC) is an emerging video coding approach in the new era, particularly attractive due to its flexibility to introduce very simple encoder structures. This feature could be very effectively utilized in the design of low cost video cameras. However, the DVC architecture commonly discussed in research literature has a fundamental drawback of involving a feedback channel between the encoder and the decoder, which restrains itself from being used in video storage based applications. In this paper, we discuss a solution to the above problem in DVC, with a novel unidirectional architecture. In the proposed design, the feedback channel is suppressed and the encoded (compressed) bit stream can be transferred onto storage media for offline processing. The proposed decoder uses the spatial and temporal properties of the video sequence to refine the side information for iterative decoding, with the repeated use of same parity bit stream. The simulation results depict a significantly improved performance over other conventional video coding techniques proposed for use in low to middle end video equipments, while involving a very low encoder complexity.

A Study on Non-octave Scalable Image Coding and Its Performance Evaluation Using Digital Cinema Test Material

JPEG2000, an international standard for still image compression, offers 1) high coding performance, 2) unified lossless/lossy compression, and 3) resolution and SNR scalability. Resolution scalability is an especially promising attribute given the popularity of Super High Definition (SHD) images like digital-cinema. Unfortunately, its current implementation of resolution scalability is restricted to powers of two. In this paper, we introduce non-octave scalable coding (NSC) based on the use of filter banks. Two types of non-octave scalable coding are implemented. One is based on a DCT filter bank and the other uses wavelet transform. The latter is compatible with JPEG2000 Part2. By using the proposed algorithm, images with rational scale resolutions can be decoded from a compressed bit stream. Experiments on digital cinema test material show the effectiveness of the proposed algorithm.

Area and Power Reduction of Embedded DSP Systems using Instruction Compression and Re-configurable Encoding

Proposes a run-time reconfiguration mechanism to map multiple instructions on a single compressed bit pattern, thus enabling significant code compression. This results in reduced area due to smaller program memory size and also reduces instruction fetch related power dissipation. We enhance Texas Instruments DSP core TMS320C27x to incorporate this mechanism and evaluate the improvements on code size and instruction fetch energy using real life embedded control application programs. We show that with minimal hardware overhead, we can reduce code size by over 10% and instruction fetch energy by over 40%.

An efficient content-adaptive motion-compensated 3-D DWT with enhanced spatial and temporal scalability

We propose a novel, content adaptive method for motion-compensated three-dimensional wavelet transformation (MC 3-D DWT) of video. The proposed method overcomes problems of ghosting and nonaligned aliasing artifacts which can arise in regions of motion model failure, when the video is reconstructed at reduced temporal or spatial resolutions. Previous MC 3-D DWT structures either take the form of MC temporal DWT followed by a spatial transform ("t+2D"), or perform the spatial transform first ("2D + t"), limiting the spatial frequencies which can be jointly compensated in the temporal transform, and hence limiting the compression efficiency. When the motion model fails, the "t + 2D" structure causes nonaligned aliasing artifacts in reduced spatial resolution sequences. Essentially, the proposed transform continuously adapts itself between the "t + 2D" and "2D + t" structures, based on information available within the compressed bit stream. Ghosting artifacts may also appear in reduced frame-rate sequences due to temporal low-pass filtering along invalid motion trajectories. To avoid the ghosting artifacts, we continuously select between different low-pass temporal filters, based on the estimated accuracy of the motion model. Experimental results indicate that the proposed adaptive transform preserves high compression efficiency while substantially improving the quality of reduced spatial and temporal resolution sequences.

An image coding scheme using SMVQ and support vector machines

To efficiently compress images, the spatial relations among image blocks to achieve low bit-rate compression has been widely adopted in these years. An example of using such spatial relations is side-match vector quantization (SMVQ). In this paper, a new technique utilizing support vector machines (SVM) to enhance the quality of images compressed by an algorithm based on SMVQ is proposed. We incorporate SVM as a part of the encoder/decoder to detect the edges across boundaries and, therefore, to further improve the accuracy in the block predicting phase, while the number of codewords available in the state codebooks can be enlarged at the same time without increasing the bit-rate. Our simulation confirms the superiority of the proposed scheme. Reasonable improvements in the resulting images were also obtained.

Spatio-temporal model-assisted very low-bit-rate coding with compatibility

We propose the concept of spatio-temporal model-assisted compatible coding, a technique that selectively encodes areas of different importance to the human eye in terms of space and time in moving images. Our motivation is the fact that eye contact and lip synchronization are very important in person-to-person communication. Several areas including the eyes and lips require different types of quality since they have different perceptual significance to human observers. For example, for the eyes, high resolution is needed for clear communication, while for the lips frequent refresh is desirable. Fully automatic algorithms are described for performing model area detection and motion tracking. An area-selective (AS) rate control scheme is proposed, in order to effect AS bit allocation. It extends prior work that dealt with only the spatial dimensions to include the temporal aspects of the video signal as well. The decoder does not need to be changed in any way although the encoder's rate control unit is modified. As a result, the scheme can be used in compliance with standards-based codecs. As the scene model is only used in the rate control module (hence the term model-assisted), the technique does not suffer from the artifacts associated with model-based coding. Extensive experimental results are provided using ITU-T H.263, addressing very low bit-rate compression (below 64 kb/s).

Optimized error protection of scalable image bit streams [advances in joint source-channel coding for images

This article focuses on FEC for scalable image coders. For various channel models, we survey recent progress made in system design and discuss efficient source-channel bit allocation techniques, with emphasis on unequal error protection. This article considered JSCC (joint source-channel coding) at the application layer only. Recent research has studied cross-layer optimization where JSCC is applied to both the application layer and the physical layer. The basic task here is to minimize the average distortion by allocating available power, subcarriers, and bandwidth among users at the physical layer and source-channel symbols at the application layer subject to a total resource constraint. Most of the JSCC systems covered in this article can be readily extended to transmit scalable compressed bit streams of video sequences and 3-D meshes. Due to the stringent delay constraints in video communications and the fact that MPEG is currently exploring a scalable video coding standard, fast JSCC algorithms are expected to play a bigger role and bring more performance gains. This article is also expected to stimulate further research efforts into JSCC and more importantly, prompt the industry to adopt some of these JSCC algorithms in their system designs, thus closing the cycle from algorithm development to implementation.

An Adaptive Compressed MPEG-2 Video Watermarking Scheme

Digital watermarking is becoming more and more important for protecting the authenticity of multimedia objects as they become easier to copy, exchange, and modify. Several watermarking schemes have been proposed in recent years, but most of them deal with still images, only some being extended over to the temporal domain for video watermarking. But again most of those approaches are applied to uncompressed video processing domain. In the subject paper, a new compressed video watermarking procedure is proposed. The developed method embeds several binary images, decomposed from a single watermark image, into different scenes of a video sequence. The spatial spread spectrum watermark is embedded directly into the compressed bit streams by modifying discrete cosine transform (DCT) coefficients. In order to embed the watermark with minimum loss in image fidelity, a visual mask based on local image characteristics is incorporated. Extensive experimental simulations demonstrate that the proposed watermarking scheme is substantially more effective and robust against spatial attacks such as scaling, rotation, frame averaging, and filtering, besides temporal attacks like frame dropping and temporal shifting.

Decentralized Estimation in an Inhomogeneous Sensing Environment

We consider decentralized estimation of a noise-corrupted deterministic parameter by a bandwidth-constrained sensor network with a fusion center. The sensor noises are assumed to be additive, zero mean, spatially uncorrelated, but otherwise unknown and possibly different across sensors due to varying sensor quality and inhomogeneous sensing environment. The classical best linear unbiased estimator (BLUE) linearly combines the real-valued sensor observations to minimize the mean square error (MSE). Unfortunately, such a scheme cannot be implemented in a practical bandwidth-constrained sensor network due to its requirement to transmit real-valued messages. In this paper, we construct a decentralized estimation scheme (DES) where each sensor compresses its observation to a small number of bits with length proportional to the logarithm of its local signal-to-noise ratio (SNR). The resulting compressed bits from different sensors are then collected and combined by the fusion center to estimate the unknown parameter. The proposed DES is universal in the sense that each sensor compression scheme requires only the knowledge of local SNR, rather than the noise probability distribution functions (pdf), while the final fusion step is also independent of the local noise pdfs. We show that the MSE of the proposed DES is within a constant factor of 25/8 of that achieved by the classical centralized BLUE estimator.