SUMMARY A camera calibration method based on the two vanishing points, which are orthogonal to each other, is presented in this paper. On the basis of the facts that the modulus constraint can provide an equation and that two equations can be obtained from two pairs of vanishing points, which are orthogonal to each other, the self‐calibration is quasilinearly realized. The experiment results with simulate data and real image sequences show that the presented method is efficient. Copyright © 2013 John Wiley & Sons, Ltd.

Spectral unmixing amounts to automatically finding the signatures of pure spectral components (called endmembers in the hyperspectral imaging literature) and their associated abundance fractions in each pixel of the hyperspectral image. Many algorithms have been proposed to automatically find spectral endmembers in hyperspectral data sets. Perhaps one of the most popular ones is the pixel purity index (PPI), which is available in the ENVI software from Exelis Visual Information Solutions. This algorithm identifies the endmembers as the pixels with maxima projection values after projections onto a large randomly generated set of random vectors (called skewers). Although the algorithm has been widely used in the spectral unmixing community, it is highly time consuming as its precision asymptotically increases. Due to its high computational complexity, the PPI algorithm has been recently implemented in several high-performance computing architectures, including commodity clusters, heterogeneous and distributed systems, field programmable gate arrays, and graphics processing units (GPUs). In this letter, we present an improved GPU implementation of the PPI algorithm, which provides real-time performance for the first time in the literature.

Correlation Noise Modeling (CNM) is a key factor to influence the performance of Distributed Video Coding (DVC). In most current CNM solutions, the distribution parameter is estimated based on the motion compensated residual frames and kept constant during the decoding process. A progressive correlation noise refinement method is proposed in this paper for transform domain Wyner-Ziv video coding to model the correlation noise more accurately, in which the estimated correlation noise is refined by using previously decoded bitplanes and quantization errors as bitplane decoding proceeds. The experimental results show that our proposed correlation noise refinement method could provide considerable bitrate savings and PSNR gains for transform domain Wyner-Ziv video coding system.

There lies a geometric relationship (homography) between two frames in the video sequences captured by pan-tilt (PT) cameras due to their constrained movement, and the geometric relationship is valuable for reducing the spatial redundancy in video coding. In this paper, we propose a novel homography-based search (HBS) algorithm for block motion estimation in coding the sequences captured by PT cameras, which well utilizes the homography between two frames. In addition, adaptive thresholds are adopted in our method to classify different kinds of blocks. Compared with other traditional fast algorithms, the proposed HBS algorithm is proved more efficient for the sequences captured by PT cameras.

Super-resolution reconstruction (SRR) deals with construction of a high-resolution image from a set of blurred, degraded and shifted low-resolution images of a scene. A variety of methods have been proposed to address the SRR problem, nevertheless they are usually based on a simple cost function thus are very sensitive to their assumed model of data and noise, which limits their utility. This paper proposes a novel SRR approach based on Bayesian estimation by minimizing a guided cost function. That is, the intensity variation is incorporated into the similarity term to guide the L1norm minimization. As the adjusted similarity term can identify the outlier in the structure area, the proposed algorithm is structure adaptive and very successful in edge-preserving. Lots of experimental results show that the proposed algorithm has considerable improvement in terms of both objective measurements and visual effects.

An adaptive threshold for early termination is proposed in this paper to enhance the cross octagonal search algorithm (COSA). In block motion estimation, search patterns have a very important impact on searching speed and distortion performance. COSA achieves almost the same visual quality with full-search algorithm while it takes much fewer search points than hybrid unsymmetrical-cross multi-hexagon-grid search (UMHexagonS) indeed. An adaptive threshold for early termination is introduced to COSA which avoids meaningless calculation after the searching point is good enough. The simulation results show that the proposed method reduces the motion estimation time by from 10.90% to 42.75% than UMHexagonS according to different types of sequences with negligible coding loss.

How to protect the video streaming for reasonable usage is a necessary technology in multimedia services over network. However, most the previous schemes are too complicated and time-consuming to apply in real multimedia content protection system. Network Coding (NC) is a new technology which codes the input information at intermediate nodes and can make the network information flow achieve the upper bound of max-flow min-cut theory. Random Linear Network Coding (RLNC) is a practical approach of NC with advantage of decentralized operation. In this paper, we proposed a novel scalable video streaming protection algorithm with an efficient packetization scheme and a distribution scheme according to authority levels of different users based on RLNC approach. The algorithm classified the packetized packets into different levels and employed three kinds of permission matrix (PM) to control the distribution of video streaming. The implementation of the proposed algorithm was described in detail to show the efficiency and low complexity of the method.

Summary form only given. Large aperture static imaging spectrometer (LASIS) is a new kind of interferometer spectrometer with the advantages of high throughput and large field of view. The LASIS data contains spatial information in principle component along spatial direction and spectral information in modulated component along Optical Path Difference (OPD) direction. LASIS data have clearly parallel displacement of spatial information among continuous frames. It is a unique characteristic for LASIS data compared with other kinds of interferometer spectrometer such as SMII data and GITFS data. Although dispersive spectrometer, such as AVIRIS data, also contains some spatial information, each frame in a group shows the same ground view with different wavelengths spectrum without any motion displacement among inter frames. Based on these characteristics, we propose a lossless data compression method named Dual-direction Prediction Vector Quantization (DPVQ). With a dual-direction prediction on both spatial and spectral direction, redundancy in LASIS data is largely removed by minimizing the prediction residue in DPVQ. Then a fast vector quantization (VQ) avoiding codebook splitting process is applied after prediction. Considering time efficiency, the dual-direction prediction and VQ in DPVQ are optimized to reduce the calculations, so that optimized prediction saves 60% running time and fast VQ saves about 25% running time with a similar quantization quality compared with classical generalized Lloyd algorithm (GLA). Experimental results, shown in Fig. 2, indicate that DPVQ can achieve a maximal Compression Ratio (CR) at about 3.4, which outperforms many existing lossless compression algorithms.

A novel object tracking algorithm is presented in this paper by using the joint color-texture histogram to represent a target and then applying it to the mean shift framework. Apart from the conventional color histogram features, the texture features of the object are also extracted by using the local binary pattern (LBP) technique to represent the object. The major uniform LBP patterns are exploited to form a mask for joint color-texture feature selection. Compared with the traditional color histogram based algorithms that use the whole target region for tracking, the proposed algorithm extracts effectively the edge and corner features in the target region, which characterize better and represent more robustly the target. The experimental results validate that the proposed method improves greatly the tracking accuracy and efficiency with fewer mean shift iterations than standard mean shift tracking. It can robustly track the target under complex scenes, such as similar target and background appearance, on which the traditional color based schemes may fail to track.

Scalable video representation of the state-of-art scalable extension of the H.264/MPEG-4 AVC (SVC) and its combined 3d scalability feature offer an excellent solution to flexible video multicast over IP network. In order to relieve the impact of the severe bandwidth fluctuations and packet loss to the reconstructed quality in heterogeneous networks like the internet, a GOP-adaptive layer-based priority ordering algorithm for SVC is proposed in this paper. The method ordered the SVC bit stream according to the rate distortion contribution of different layer to the whole performance within a GOP, which makes the transmission more efficient and robust under the same bandwidth condition. Simulation results of different sequences are given to demonstrate that the proposed algorithms offer better performance in video quality as compared the default SVC ordering method and the SNR-based ordering method.

Wyner-Ziv (WZ) video coding, or lossy coding of video with decoder side information (SI), is a new video coding paradigm which provides the potential of shifting encoder complexity to decoder. Due to the fact that correlation among adjacent frames varies spatially and temporally in a video sequence, in WZ video coding, the quality of SI generated at the decoder also varies accordingly. This implies that more parity bits should be sent for locations where the quality of the SI is poor, while fewer parity bits for locations where the quality of the SI is good. For this reason, this paper proposes a WZ video coding scheme with block classification. In the scheme, according to difference between blocks in a WZ frame and its adjacent key frame, the blocks in a WZ frame are classified into classes of different importance. A strategy is designed so that the more important a class is, the more bits will be transmitted for it, and this leads to savings in bit rate. Simulation on various test video sequences shows that, compared to a similar scheme without block classification, the proposed scheme can achieve a bit rate savings of up to 42.44% with only slight PSNR loss in some cases.

The interferential spectrometer is considered as the next generation of imaging spectrometers in aerial remote sensing. The customary multispectral images compression methods only consider the quality of reconstructed images in spatial domain without concerning the effect in Fourier domain where the application of spectrum is often used, such as substance classification and recognition. Our method WRDO-SPIHT (weighted rate-distortion optimization for SPIHT) is proposed based on the relationship between the distortion in Fourier domain and compression in spatial domain.

In this paper, we propose a Wyner-Ziv video coding scheme with spatio-temporal side information. In the scheme, temporal side information is generated through motion compensated temporal interpolation, using frames that are already decoded. While spatial side information is created through spatial prediction, using the temporal side information. The spatio-temporal side information are both incorporated into a turbo code based Slepian-Wolf decoder to decode the quantized source, but only temporal side information is used for reconstruction. Extensive simulations over various test video sequences show, compared with a similar codec with only temporal side information, the proposed scheme can achieve more than 20% bit rate savings without sacrifice in PSNR, and hence significantly improves the coding efficiency.

To overcome drawbacks of the low complexity multiple description (MD) video coding method which we presented in a previous paper, we propose an improved MD video coding method in this paper. The previous method consists of three integral components, namely GOB alternation, motion information duplication, and low quality macroblock update, in which the first two components establish a basic MD coding framework, and the last one makes redundancy in a controllable way. The method has very good performance and a relatively lower complexity. However, the method can not reach as large a redundancy region as some other MD video coding methods. One cause is that duplicating motion in both the descriptions introduces much redundancy for video sequences with slower motion. Another cause is that with limited quantization parameter range specified by the video coding standards, the lowest redundancy region which low quality macroblock update can reach is limited too. This paper addresses the problems by introducing two additional coding modes for a low quality inter macroblock, both modes take into account strategies a decoder will take for error concealment. The two modes take only 2 bits each to indicate in the bit stream, so redundancy introduced by motion duplication and low quality macroblock update is greatly reduced. A rate distortion criterion is used for choosing which mode to use for a particular low quality inter macroblock. Simulation results show, with some increment in computational complexity, the new method achieves even better performance than the previous approach both in terms of redundancy rate distortion, and in packet loss scenario. The new method can also reach a much lower redundancy region.

A new error resilient method based on data partitioning and unequal error protection for H.264 video transmission over wireless network is proposed in this paper. By introducing the Impact factor of Inter MB and /spl rho/-curve, the method further divides the C type partition into several subtypes according to their effects to error propagation, then unequal error protection are applied to each partition including that of A, B and C partition. The theoretical model of rate allocation and a fast bidirectional local search algorithm based on iteratively improvement are also presented. The simulation results show that our proposed approach can achieve better results than conventional H.264 coding method (about 0.2-0.6 dB's gain in PSNR) when transmitting over wireless channel and can obtain more graceful degradation with the increasing of packet loss rate.

Summary form only given. This paper proposes a new partition method for reliable H.264 video transmission over wireless channels wherein the impact of each inter MB to error propagation is analyzed. A relationship between image quality and the correctly received MB is established and this helps the encoder find the truncation point to satisfy the quality requirement. The inter partition (or C type) data are further divided into several partitions, then unequal error protection (UEP) can be applied to them with the use of the priority encoding transmission (PET) method. The use of a new fast iteratively improved bidirectional local search algorithm is suggested. Simulation results show that the proposed approach can achieve better results than conventional H.264 coding method when transmitting over wireless channel and can obtain more graceful degradation with the increasing of packet loss rate.

This paper proposes a novel fuzzy reasoning interpolation method for video deinterlacing. We propose SMDW and TMDW parameters to measure the amount of entropy in the spatial and temporal domains. The shape of the membership function is designed adaptively according to the parameters, and can be utilized to determine edge direction. Our proposed fuzzy edge direction detector follows three processing steps: fuzzification, rule inference, and defuzzification. This filter operates by identifying small pixel variations in nine orientations (0°, ±30°, ±45°, ±55°, and ±60°) in each domain, and works by using rules to infer the edge direction. Detection and interpolation results are presented. The results of computer simulations show that the proposed method is able to outperform a number of methods in the literature.

DWT has been the basis of image compression, such as in JPEG2000. This paper proposes a novel VLSI architecture that performs line-based DWT using a lifting scheme. The architecture consists of row processors, column processors, an intermediate buffer and a control module. The intermediate buffer is composed of FIFOs to store temporary results of horizontal filters. The control module schedules the output of wavelet coefficients to external memory with the priority from high to low. Horizontal filtering and vertical filtering are simultaneous, and all levels of DWT are processed parallel. The presented architecture finishes multi levels of 9/7 DWT in one image transmission time. Meanwhile, it decreases significantly memory used and hardware resource required. This architecture is suitable for various real-time image/video applications.

In this paper, we present a new multiple description video coding method. It starts from GOB alternation to create two descriptions for each frame encoded, carriage of motion information in both descriptions helps to improve the quality of single channel reconstruction, and a process called low quality macroblock update helps to not only further improve the quality of single channel reconstruction but also reduce the mismatch between the encoder and decoder. The advantages of the proposed approach include: effectiveness, which has better performance than the well known MDTC video coder both in terms of redundancy rate distortion, and in the packet loss scenario; low complexity, and standard compliant to the extent that each description can be decoded by a standard video decoder.

A new method combining source channel coding with source modeling and network congestion control for reliable video transmission over wireless network is proposed in this paper. Based on scene modeling and characteristic analyzing, all layers generated by scalable coding are classified into several types and two queuing are made respectively according to their contribution to network congestion and to the quality of reconstructed video. Then the source rate, protection level and congestion control strategy are dynamically adjusted according to different error status in which the packet loss is caused by network congestion or by unreliable transmission in wireless channel. The simulation results show that our proposed approach can achieve better results than MPEG-4 video source coding with fix rate Turbo coding and than the one which dynamically adjusting source coding and channel coding rates only.

H.264/AVC encoder complexity is remarkable due to mainly variable block size ME and exhaustive RDO mode decision. This makes application of H.264/AVC in network especially wireless environments very difficult. To reduce encoder complexity, statistical characteristics of modes among adjacent macroblocks (MBs) spatially and temporally are first studied using H.264 reference software. Then a fast algorithm is presented to reduce jointly the computational load of mode decision and ME. The main ideas are as follows: (1) candidate modes for current MB are first inferred from mode and motion information of defined reference MBs and then partial RDO approach is applied to make target selection; (2) ME is considered as a part of mode decision and no ME is required for particular modes that are eliminated in advance; (3) the exhaustive RDO method is invoked only if average distortion of the reference MBs goes beyond a predefined threshold. Simulation results demonstrate that our scheme can reduce encoder complexity significantly while coding efficiency is only slightly decreased.

In this paper, we first propose a multiple description mesh-based motion coding method, which generates two descriptions for mesh-based motion by first subsampling the nodes of a right-angled triangular mesh and then dividing them into two groups. Motion vectors associated with the mesh nodes in each group form the mesh-based motion field for each description, and are transmitted over distinct network channels. With the nodes in each group, two other regular triangular meshes besides the original one can be constructed, and three different prediction images can be reconstructed according to descriptions available. The proposed multiple description mesh-based motion coding method is then combined with the pairwise correlating transform proposed in Y. Wang et al. (1997), and a new and complete multiple description video coding scheme is proposed. Further measures are taken to reduce the mismatch between the encoder and the decoder that occurs when the decoder receives only one of the two descriptions and has to use a different reference frame for motion compensation other than the encoder does. Simulations were carried out to evaluate the performance of the proposed scheme, and the results show, compared to the MDTC video coding method in A. Reibman et al. (2002), the proposed scheme has achieved lower redundancy rate distortion; in the scenario of packet loss, the proposed scheme outperforms the MDTC video coding method.

A new combined multiple description and layered coding method based on adaptive frame insertion (AFl-MDLC) for transmission of video bit stream over wireless ad-hoc network is proposed in this paper. The main idea of the method is to adaptively insert the transition frames according to the relative motion between two neighboring frames, and then divide the video sequence into two descriptions with independent prediction loops. Afterwards, the base layer and the enhancement layer bit stream for each description are generated and transmitted across wireless network, which is modeled with finite state Markov process. A multiple-path transmitting strategy is presented for the AFI-MDLC data packets according to the characteristics of ad hoc multi-hop wireless network. The experimental results show that the method can help the decoder recover from packet loss more quickly as compared with the previous methods, and provides more stable and better quality for the reconstruction of video sequence.

Based on video scene segmentation and 3D wavelet transform, a watermarking procedure for digital video, with spatial-temporal embedding and blind detecting algorithm, is presented in This work. First, a watermark image as copyright sign is preprocessed with a random location matrix. According to the characteristics of the video data, the preprocessed watermark image is adaptively spread spectrum and added into the 3D wavelet coefficients of the video shot. The proposed watermark procedure needs two keys: a random location matrix and spread spectrum watermark sequence. The first one ensures the security of watermarking procedure and the second one guarantees its robustness. The experimental results demonstrate the effectiveness and robustness of our video watermarking procedure against several video degradations and watermarking attacks.

A fast algorithm for T/sub 2/ encoder in JPEG2000 suitable for hardware implementation is presented in this paper, based on the elaborate analysis of a rate-distortion optimization algorithm. By reducing calculative complexity, the difficulty of hardware implementation for the T/sub 2/ encoder is reduced, and the parallelizability of the JPEG2000 hardware system is enhanced. The experimental results show that the final code stream is in accordance with the standard format of JPEG2000 and reconstructed image quality decreases little. The system has been implemented on FPGA.

A new revised multiple description SPIHT coding is proposed to combat packet loss. According to the region of interest of human eyes, the method reorders the zero trees of wavelets and assigns different coding rates to redundant trees. Simulation results show that the method can improve the image quality both objectively and subjectively compared to other multiple description coding methods in the case of packet loss.

A camera under general motions allows the fixed geometric entities: the absolute conic and the plane at infinity to be determined uniquely for self-calibration. For turntable motions, these two geometric entities cannot be determined, and will lead to ambiguities in 3D reconstruction. However, some fixed points and lines will arise as a result of turntable motions, and can be related to the calibration matrix. We have made two contributions for self-calibration under turntable motion. First, a detailed theoretical analysis of degeneracy is given, and the degrees of the resulting ambiguities are deduced. Second, from some constraints on the physical characteristics of the camera the ambiguities can be removed up to a single parameter family. Experiments on real turntable image sequences verified our findings which are used also to perform a 3D reconstruction.

A novel effective regional descriptor based on the normalized rapid descriptor (NRD) and regional projections is presented. The NRD is significantly superior to the normalized Fourier descriptor (NFD) in computational speed and storage requirement. The proposed descriptor was used for shape analytical experiments for several types of synthesized images. The descriptor was applied to the target recognition of four sequential images varying in size and orientation relative to the sensor. The results show that the descriptor is quite effective.>