Rate-distortion Criterion Research Articles

A new paradigm for high-capacity reversible data hiding with pixel repetition and adaptive embedding

Reversible data hiding (RDH) offers a useful attribute of retaining the visual semantics with security properties, for the effective management and protection of digital images with their metadata. This paper introduces a Reversible Data Hiding (RDH) scheme with Pixel Repetition (PR) to selectively embed additional secret data. bits utilizing the image redundancy created with PR. A generalized framework of PR is first developed and the rate–distortion criterion is extended for adaptive embedding. An input image is defined to be scaled-up by replacing each original pixel (called seed) with a block of shape s×s containing the seed, where s is the scaling factor. For better utilizing this PR-based image redundancy, we then propose an RDH scheme with two-phase embedding for s=2. The first phase of the scheme embeds 4-bit data in each 2 × 2 image block using a mapping function, which is designed to modify the repeated pixels, keeping the seed intact in each block. Being invertible, the mapping function also allows another phase of embedding in the preserved seeds using an adaptive selection of their least significant bits. Compared to the prominent PR-based and other related schemes, an impressive rate–distortion performance of the proposed scheme is recorded with a greater potential for the applications that require a high and varying embedding rate with better image quality.

Low-Complexity Rate-Distortion Optimization of Sampling Rate and Bit-Depth for Compressed Sensing of Images.

Compressed sensing (CS) offers a framework for image acquisition, which has excellent potential in image sampling and compression applications due to the sub-Nyquist sampling rate and low complexity. In engineering practices, the resulting CS samples are quantized by finite bits for transmission. In circumstances where the bit budget for image transmission is constrained, knowing how to choose the sampling rate and the number of bits per measurement (bit-depth) is essential for the quality of CS reconstruction. In this paper, we first present a bit-rate model that considers the compression performance of CS, quantification, and entropy coder. The bit-rate model reveals the relationship between bit rate, sampling rate, and bit-depth. Then, we propose a relative peak signal-to-noise ratio (PSNR) model for evaluating distortion, which reveals the relationship between relative PSNR, sampling rate, and bit-depth. Finally, the optimal sampling rate and bit-depth are determined based on the rate-distortion (RD) criteria with the bit-rate model and the relative PSNR model. The experimental results show that the actual bit rate obtained by the optimized sampling rate and bit-depth is very close to the target bit rate. Compared with the traditional CS coding method with a fixed sampling rate, the proposed method provides better rate-distortion performance, and the additional calculation amount amounts to less than 1%.

Optimized Data Representation for Interactive Multiview Navigation

In contrary to traditional media streaming services where a unique media content is delivered to different users, interactive multiview navigation applications enable users to choose their own viewpoints and freely navigate in a 3-D scene. The interactivity brings new challenges in addition to the classical rate-distortion trade-off, which considers only the compression performance and viewing quality. On the one hand, interactivity necessitates sufficient viewpoints for richer navigation; on the other hand, it requires to provide low bandwidth and delay costs for smooth navigation during view transitions. In this paper, we formally describe the novel trade-offs posed by the navigation interactivity and classical rate-distortion criterion. Based on an original formulation, we look for the optimal design of the data representation by introducing novel rate and distortion models and practical solving algorithms. Experiments show that the proposed data representation method outperforms the baseline solution by providing lower resource consumptions and higher visual quality in all navigation configurations, which certainly confirms the potential of the proposed data representation in practical interactive navigation systems.

Light Field Image Coding Using High-Order Intrablock Prediction

This paper proposes a two-stage high-order intrablock prediction method for light field image coding. This method exploits the spatial redundancy in lenslet light field images by predicting each image block, through a geometric transformation applied to a region of the causal encoded area. Light field images comprise an array of microimages that are related by complex geometric transformations that cannot be efficiently compensated by state-of-the-art image coding techniques, which are usually based on low-order translational prediction models. The two-stage nature of the proposed method allows us to choose the order of the prediction model most suitable for each block, ranging from pure translations to projective or bilinear transformations, optimized according to an appropriate rate-distortion criterion. The proposed higher order intrablock prediction approach was integrated into a high efficiency video coding (HEVC) codec and evaluated for both unfocused and focused light field camera models, using different resolutions and microlens arrays. Experimental results show consistent bitrate savings, which can go up to 12.62%, when compared to a lower order intrablock prediction solution and 49.82% when compared to HEVC still picture coding.

Adaptive Color-Space Transform in HEVC Screen Content Coding

The screen content coding (SCC) Extensions of high efficiency video coding (HEVC) employs in-loop adaptive color-space transform (ACT) technique to explore the inter-color-component redundancy, i.e., statistical redundancy among different color components. In ACT, the prediction residual signal is adaptively converted into a different color space, i.e., YCgCo. The rate-distortion criteria is employed to decide whether to code the residual signal in the original color space or YCgCo color space. Typically, the inter-color-component correlation could be reduced when ACT is enabled. The residual signal after possible color-space conversion is then coded, following the existing HEVC framework, i.e., transform if necessary, quantization and entropy coded. This paper describes the design of ACT from several points of view, from theoretical analysis to implementation details. Experimental results are also provided to demonstrate the significant coding gains of ACT in the HEVC SCC Extensions.

Merge Frame Design for Video Stream Switching Using Piecewise Constant Functions.

The ability to efficiently switch from one pre-encoded video stream to another (e.g., for bitrate adaptation or view switching) is important for many interactive streaming applications. Recently, stream-switching mechanisms based on distributed source coding (DSC) have been proposed. In order to reduce the overall transmission rate, these approaches provide a merge mechanism, where information is sent to the decoder, such that the exact same frame can be reconstructed given that any one of a known set of side information (SI) frames is available at the decoder (e.g., each SI frame may correspond to a different stream from which we are switching). However, the use of bit-plane coding and channel coding in many DSC approaches leads to complex coding and decoding. In this paper, we propose an alternative approach for merging multiple SI frames, using a piecewise constant (PWC) function as the merge operator. In our approach, for each block to be reconstructed, a series of parameters of these PWC merge functions are transmitted in order to guarantee identical reconstruction given the known SI blocks. We consider two different scenarios. In the first case, a target frame is first given, and then merge parameters are chosen, so that this frame can be reconstructed exactly at the decoder. In contrast, in the second scenario, the reconstructed frame and the merge parameters are jointly optimized to meet a rate-distortion criteria. Experiments show that for both scenarios, our proposed merge techniques can outperform both a recent approach based on DSC and the SP-frame approach in H.264, in terms of compression efficiency and decoder complexity.

The Rate-Distortion Optimized Compressive Sensing for Image Coding

Compressive Sensing (CS) is an emerging technology which can encode a signal into a small number of incoherent linear measurements and reconstruct the entire signal from relatively few measurements. Different from former coding scheme which distortion mainly comes from quantizer, distortion and bit rate are related to quantization and compressive sampling in the compressive sensing based image coding schemes. Moreover, the total number of bits is often constrained in the practical application. Therefore under the given bit rate how to balance the number of measurements and quantization step size to minimization the distortion is a great challenge. In this paper, a fast Lagrange multiplier solving method is proposed for the compressive sensing based image coding scheme. Then using the solved Lagrange multiplier, the optimal number of measurements and quantization step size are determined based on the rate-distortion criteria. Experimental results show that the proposed algorithm improves objective and subjective performances substantially.

Robust Transmission of Scalable Video Coding Bitstream Over Heterogeneous Networks

Video transmission using Scalable Video Coding (SVC) enables the functionalities of adaptation for both channel bandwidth and terminal device. However, link adaptation, which requires the video bitstream to provide error resilient scalability (ERS), is currently not supported in SVC. In this paper, we propose a robust SVC bitstream transmission framework, which integrates both error resilient (ER) coding and error concealment (EC) to enable the desired link adaptability. First, at the encoder, we design an ER coding scheme for SVC using redundant pictures, in which redundant picture information (RPI) is generated under rate-distortion criteria and transmitted to the media gateway together with the SVC bitstream. Then, ERS can be effectively achieved at the media gateway by selectively adding or removing coded pictures of different video coding layers according to the RPI and current network link status. Finally, at the decoder, we take advantage of the unique characteristics of SVC to develop an EC scheme based on both the proposed Virtual-BLSkip method and Wiener filtering to recover the lost or removed enhancement layer pictures. The proposed framework has negligible impact on the coding efficiency because it transmits RPIs rather than directly adding redundancy into the original bitstream. More importantly, it successfully strikes a balance between coding efficiency, error resiliency, and operation complexity. It is capable of providing the desired ERS with extremely low complexity, and maintaining virtually the same bit rate as input video bitstream. The experimental results show that the proposed framework achieves significant performance gains over existing ER transmission schemes.

A Novel Distortion Model and Lagrangian Multiplier for Depth Maps Coding

In three-dimensional videos (3-DV) coding systems, depth maps are not used for viewing but for rendering virtual views. Therefore, the traditional rate distortion criterion (including distortion criterion, and Lagrangian multiplier) is not suitable for depth map coding. In order to design an effective rate distortion criterion for depth maps, the relationship between the distortion of synthesized virtual view and the coding error of depth maps is analyzed in detail. Through the analysis, a polynomial model revealing the relationship between the coding error of depth maps and the distortion of synthesized virtual view is derived. Model parameters are estimated by utilizing camera parameters and features of the texture video corresponding to the depth map. Based on the model, a virtual view-based Lagrangian multiplier for depth map coding is also proposed. Experimental results demonstrated the accuracy of the model. The squared correlation coefficients between the actual distortion of virtual view and the estimated distortion are all larger than 0.98 for all tested sequences. When incorporating the proposed model and Lagrangian multiplier into the mode decision procedure of joint model version 18.5 (JM18.5) of H.264/AVC, a maximum 0.470 dB BD PSNR and an average 0.251 dB BD PSNR can be achieved.

Compression of encrypted images with multi-layer decomposition

This work proposes a novel scheme of lossy compression for encrypted gray images. In the encryption phase, the original image is decomposed into a sub-image and several layers of prediction errors, and the sub-image and prediction errors are encrypted using an exclusive-or operation and a pseudo-random permutation, respectively. Although a channel provider does not know the cryptographic key and the original content, he can still effectively reduce the amount of encrypted data by quantizing the permuted prediction errors on various layers, and an optimization method with rate-distortion criteria can be employed to select the values of quantization steps. At receiver side with the knowledge of cryptographic key, a decoder integrating dequantization, decryption and image reconstruction functions is used to retrieve the principal content of original image from the compressed data. Experimental result shows the rate-distortion performance of the proposed scheme is significantly better than that of previous technique.

Affine Model Based Motion Compensation Prediction for Zoom

Zoom motion is classified into two categories, i.e., global zoom motion and local zoom motion. A simple affine motion model with four parameters is utilized to describe zoom motion efficiently based on the analyses of camera imaging principles. Based on the motion model, a basic candidate motion vector (BCMV) of a block could be derived when model parameters are confirmed. Then a set of candidate motion vectors (CMVs) could be obtained by modifying the BCMV. Thereafter, template matching is used to choose the optimal CMV (OCMV). Finally, the block is coded with the optimal CMV as an independent mode, and a rate distortion (RD) criterion is used to determine whether to use the mode or not. Experimental results demonstrate that by implementing the proposed method into Key Technology Area test platform version 2.6r1 (KTA2.6r1), a maximum -21.99% and average -8.72% bit rate savings can be achieved for videos involving zoom motion, while maintaining the same quality (evaluated by PSNR) of reconstructed videos when IPPPP coding structure is used. When Hierarchical B coding structure is employed, the maximum and average bit rate savings are - 10.48% and - 5.575% when the qualities of reconstructed videos remain unchanged. Besides, for videos involving camera rotation, translation, etc., an average -2.04% bit rate savings could also be achieved; while for videos containing common motions, an average -1.19% bit rate saving could be achieved at the same quality of reconstructed videos.

Rate-Distortion Optimized Cross-Layer Rate Control in Wireless Video Communication

A wireless video communication system can be designed based on the rate-distortion (R-D) criterion, i.e., minimizing the end-to-end distortion (which includes quantization distortion and transmission distortion) subject to the transmission bit-rate constraint. The minimization can be achieved by adjusting the source encoding parameters and channel encoding parameters. This rate-distortion optimization (RDO) is usually done for each video frame individually in a real-time video communication system, e.g., video calls or videoconferencing. To achieve this, an accurate bit-rate model and distortion model for each frame can be used to reduce the RDO complexity. In this paper, we derive a source bit-rate model and quantization distortion model; we also improve the performance bound for channel coding under a convolutional code and a Viterbi decoder, and derive its performance bound under a Rayleigh block fading channel. Given the instantaneous channel condition, e.g., signal-to-noise ratio and transmission bit-rate constraint, we design an R-D optimized cross-layer rate control (CLRC) algorithm by jointly choosing quantization step size in source coding and code rate in channel coding. Experimental results show that our proposed R-D models are more accurate than the existing R-D models. Experimental results also showed that the rate control under our models has more stable R-D performance than the existing rate control algorithms; using the channel estimation, CLRC can further achieve remarkable R-D performance gain over that without channel estimation. Another important result is that the subjective quality of our CLRC algorithm is much better than the existing algorithms due to its intelligent reference frame selection.

Image Compression Using Sparse Representations and the Iteration-Tuned and Aligned Dictionary

We introduce a new image coder which uses the Iteration Tuned and Aligned Dictionary (ITAD) as a transform to code image blocks taken over a regular grid. We establish experimentally that the ITAD structure results in lower-complexity representations that enjoy greater sparsity when compared to other recent dictionary structures. We show that this superior sparsity can be exploited successfully for compressing images belonging to specific classes of images (e.g., facial images). We further propose a global rate-distortion criterion that distributes the code bits across the various image blocks. Our evaluation shows that the proposed ITAD codec can outperform JPEG2000 by more than 2 dB at 0.25 bpp and by 0.5 dB at 0.45 bpp, accordingly producing qualitatively better reconstructions.

Texture video-assisted motion vector predictor for depth map coding

A texture video-assisted motion vector predictor for depth map coding is proposed in this letter. Based on the analyses of motion similarity between texture videos and their corresponding depth maps, the proposed approach uses the motion vectors of texture videos and the median predictor jointly to determine the optimal predicted motion vector for depth map coding by employing a rate-distortion (R-D) criterion. Experimental results demonstrate that compared with the median predictor utilized in H.264/AVC, the proposed method can save the maximum and average bit rate as high as 4.89% and 3.68%, respectively, while guaranteeing the quality of synthesized virtual views.

Satellite image compression by concurrent representations of wavelet blocks

This paper proposes a complete compression and coding scheme for on-board satellite applications considering the main on-board constraints: low computational power and easy bit rate control. The proposed coding scheme improves the performance of the current Consultative Committee for Space Data Systems (CCSDS) recommendation for a low additional complexity. We consider post-transforms in the wavelet domain, select the best representation for each block of wavelet coefficients, and encode it into an embedded bit stream. After applying a classical wavelet transform of the image, several concurrent representations of blocks of wavelet coefficients are generated. The best representations are then selected according to a rate-distortion criterion. Finally, a specific bit-plane encoder derived from the CCSDS recommendation produces an embedded bit stream ensuring the easy rate control required. In this article, both the post-transforms and the best representation selection have been adapted to the low complexity constraint, and the CCSDS coder has been modified to compress post-transformed representations.

All-optical KarhunenLoeve Transform Using Multimode Interference Structures on Silicon Nanowires

A variety of unitary transforms have attracted considerable attention for their application in data, image compression and other signal processing applications. Among many transforms, the KarhunenLoeve transform (KLT) is known to be optimal because of its advantages of computational efficiency, residual correlation and rate distortion criterion. In this paper, it is shown that the all-optical KarhunenLoeve transform can be realized using multimode interference (MMI) structures on silicon wire waveguides. The transfer matrix method (TMM) and the beam propagation method (BPM) are used to verify and optimally design the proposed devices.

Model Based Motion Vector Predictor for Zoom Motion

As zoom motion is common in video applications, a linear motion model is derived to describe zoom motion based on the analyses of camera imaging principles. Based on the motion model, a motion vector predictor for videos involving zoom motion is proposed. A rate distortion (RD) criterion is used to choose the optimal motion vector predictor between the one utilized in H.264/AVC and the one derived from the linear motion model. Experimental results demonstrate that by implementing the proposed method into Key Technology Area test platform version 2.2r1(KTA2.2r1), the maximum and average bit rate savings can be achieved as high as 7.66% and 4.90% respectively, while maintaining the same quality of reconstructed videos.

Efficient Spectrum Sensing With Dyadic Tree Partitioning

A low-complexity spectrum-sensing method that is based on dyadic (binary) tree partitioning is proposed. For this purpose, first, a representation of the spectrum occupation with a dyadic tree is developed. Then, the accuracy of this representation is evaluated through a rate-distortion criterion. Using this criterion, a pruning algorithm for the dyadic tree that minimizes the number of sensing operations for a predetermined value of sensing accuracy is conceived. After tailoring the pruning algorithm to the missed-detection and collision requirements of the opportunistic access, an adaptive version that performs efficient sensing in slowly varying environments is proposed. The proposed algorithm is tested on real spectrum measurements taken in the 400-910-MHz range. The sensitivity of the proposed algorithm to sensing imperfections is also evaluated. The obtained results demonstrate that the proposed algorithm provides a mean distortion of 11.4% and a mean collision probability of 5.6% for sensing only 30% of the total spectrum. A comparison with conventional energy-based detection highlights a gain of 50% in terms of the number of required measurements per channel in the low-signal-to-noise-ratio (SNR) region, where conventional energy detection is known to have poor detection performance.

A rate-distortion based quantization level adjustment algorithm in block-based video compression

In this paper, a rate-distortion based quantization level adjustment (RDQLA) algorithm is presented. Based on the rate-distortion criterion, the quantization level adjustment algorithm effectively improves coding efficiency by adaptively optimizing quantization levels of the signals near the boundaries of quantization cells and adjusting quantization levels per block. In addition, it has no overhead and is fully compatible with the existing compression standards. The proposed algorithm can be applied in any block based image and video coding method. In particular, the algorithm has been verified on the platform of H.264. Experimental results show that the proposed algorithm improves objective and subjective performances substantially. It is shown that the proposed algorithm has a gain of several dB comparing with the newest H.264 standard for high bit rates.

Fine-Granular Motion Matching for Inter-View Motion Skip Mode in Multiview Video Coding

As motion of neighboring views is highly correlated in multiview video systems, the inter-view motion skip mode has been proposed to improve the efficiency of multiview video coding (MVC) by reusing the motion information of neighboring views. To fully exploit the inter-view motion correlation, a fine-granular motion matching algorithm for the motion skip mode is presented in this paper. The proposed algorithm searches for the best matching motion information in neighboring views with fine granularity, and then uses the motion information for the motion-compensated coding in the motion skip mode. The rate-distortion optimization criterion is applied to find the best matching motion information. Experimental results show that the proposed algorithm can improve the performance of the motion skip mode, and further improve the efficiency of MVC.