Predictive RD optimized motion estimation for very low bit-ratevideo coding

Predictive rate-distortion (RD) optimized motion estimation techniques are studied and developed for very low bit-rate video coding. Four types of predictors are studied: mean, weighted mean, median, and statistical mean. The weighted mean is obtained using conventional linear prediction techniques. The statistical mean is obtained using a finite-state machine modeling method based on dynamic vector quantization. By employing prediction, the motion vector search can then be constrained to a small area. The effective search area is reduced further by varying its size based on the local statistics of the motion field, through using a Lagrangian as the search matching measure and imposing probabilistic models during the search process. The proposed motion estimation techniques are analyzed within a simple DCT-based video coding framework, where an RD criterion is used for alternating among three coding modes for each 8×8 block: motion only, motion-compensated prediction and DCT, and intra-DCT. Experimental results indicate that our techniques yield very good computation-performance tradeoffs. When such techniques are applied to an RD optimized H.263 framework at very low bit rates, the resulting H.263 compliant video coder is shown to outperform the H.263 TMN5 coder in terms of compression performance and computations simultaneously     

Multiview image coding using depth layers and an optimized bit allocation

In this paper, we present a novel wavelet-based compression algorithm for multiview images. This method uses a layer-based representation, where the 3-D scene is approximated by a set of depth planes with their associated constant disparities. The layers are extracted from a collection of images captured at multiple viewpoints and transformed using the 3-D discrete wavelet transform (DWT). The DWT consists of the 1-D disparity compensated DWT across the viewpoints and the 2-D shape-adaptive DWT across the spatial dimensions. Finally, the wavelet coefficients are quantized and entropy coded along with the layer contours. To improve the rate-distortion performance of the entire coding method, we develop a bit allocation strategy for the distribution of the available bit budget between encoding the layer contours and the wavelet coefficients. The achieved performance of our proposed scheme outperforms the state-of-the-art codecs for several data sets of varying complexity.     

Significant bit-plane clustering technique for JPEG2000 image coding

The bit-plane clustering technique is applied to high-energy code blocks to enhance the energy compaction by rearranging the column positions in these code blocks. The energy compaction effect can improve the coding efficiency of JPEG2000, which results in an improvement of 6.88% bit-rate reduction at 0.1 bpp on average over JPEG2000.     

Optimal progressive lossless image coding using reduced pyramids with variable decimation ratios

This article introduces a novel method for the construction of extended reduced pyramids with rational decimation ratios from stage to stage. It is shown that this construction produces more accurate interpolation, and thus more efficient lossless compression, than conventional reduced pyramids.     

Side-match tree-structured vector quantiser for image progressive coding

The balanced tree-structured vector quantiser is the traditional method of achieving image progressive coding. During image progressive coding, an image is decoded step-by-step in a decoder. The author proposes an unbalanced tree-structured vector quantiser to perform image progressive coding for a given series of rate thresholds. Side-match vector quantisation and its variants have been proposed to reduce the bit rate in image coding. The tree-structured vector quantiser and the side-match vector quantiser are combined to perform image progressive coding, achieving a better coding quality than that obtained using only the tree-structured vector quantiser at the same bit rate.     

Hybrid fractal image coding with quadtree-based progressive structure

A progressive structure which takes the quadtree depth into consideration is proposed for fractal image coding. Simulation results show that its image quality at different received data rates is better than that without considering the quadtree level. Then, a hybrid fractal image coding scheme based on traditional and no-search fractal image coding with the proposed progressive structure is suggested. The image quality and compression ratio can be controlled by a threshold, which makes it downward compatible to the no-search fractal image coding. Experimental results justify that the progressive performance of the proposed scheme is better than that of traditional fractal image coding.     

JPEG image encryption using fuzzy PN sequences

The recent explosion in multimedia and networking application places a great demand on efficient transmission of images at low bit rate with high security. Mixing several existing standard encryption techniques with image encoding tends to change the compression ratio greatly. In this paper, a novel image encryption algorithm is embedded as a part of JPEG image encoding scheme to meet three major necessities: (1) to provide temporal security against casual observer, (2) to preserve the compression ratio, (3) remain compliant with the JPEG file format. In the proposed algorithm, the modified DCT blocks are confused by a fuzzy PN sequence. In addition to that, the DCT coefficients of each modified DCT block are converted to unique uncorrelated symbols, which are confused by another fuzzy PN sequence. Finally, the variable length encoded bits are encrypted by chaotic stream cipher. An amalgamation of all the three techniques with random combination of seeds will provide the required security against the casual listener/observer where the security needed is only in-terms of few hours.     

Modified JPEG Huffman coding

It is a well observed characteristic that when a DCT block is traversed in the zigzag order, the AC coefficients generally decrease in size and the run-length of zero coefficients increase in number. This article presents a minor modification to the Huffman coding of the JPEG baseline compression algorithm to exploit this redundancy. For this purpose, DCT blocks are divided into bands so that each band can be coded using a separate code table. Three implementations are presented, which all move the end-of-block marker up in the middle of DCT block and use it to indicate the band boundaries. Experimental results are presented to compare reduction in the code size obtained by our methods with the JPEG sequential-mode Huffman coding and arithmetic coding methods. The average code reduction to the total image code size of one of our methods is 4%. Our methods can also be used for progressive image transmission and hence, experimental results are also given to compare them with two-, three-, and four-band implementations of the JPEG spectral selection method.     

一种基于JPEG2000的自适应联合信源信道编码方法

针对JPEG2000图像在噪声条件未知的信道上有效和可靠传输问题,本文提出了一种基于反馈的自适应联合信源信道编码方案.首先采用基于子空间的信噪比估计方法实时估计信道的信噪比SNR,进而求得信道的误码率,解决了对信道的自适应问题.其次,充分利用了JPEG2000的码流质量分级特点,建立了实用的目标函数,从而根据数据包对重建图像贡献的不同,实施不同的保护,以低复杂度的运算实现了码率优化分配的自适应过程.仿真结果表明,和现有的联合信源信道编码算法相比,这种自适应联合优化编码方法可以取得较好的效果.     

Digital image coding using legendre transform

Image coding can be implemented through DPCM, transform, hybrid, or segmentation coding techniques. Some transform coding techniques, such as cosine and Hadamard, have been exhaustively analyzed and evaluated, while others, such as Legendre, have not. This paper introduces the use of Legendre transform in image coding. The transform matrix for different block sizes is calculated, the fast algorithm is derived, and the performance is evaluated through both mean square error and subjective quality. The results obtained have indicated that the system performance is comparable with that of optimum KLT and cosine transforms; moreover, it is simpler in implementation.     

Adaptive image coding using spectral classification

We present a new classification scheme, dubbed spectral classification, which uses the spectral characteristics of the image blocks to classify them into one of a finite number of classes. A vector quantizer with an appropriate distortion measure is designed to perform the classification operation. The application of the proposed spectral classification scheme is then demonstrated in the context of adaptive image coding. It is shown that the spectral classifier outperforms gain-based classifiers while requiring a lower computational complexity.     

Jointly optimized spatial prediction and block transform for video and image coding

This paper proposes a novel approach to jointly optimize spatial prediction and the choice of the subsequent transform in video and image compression. Under the assumption of a separable first-order Gauss-Markov model for the image signal, it is shown that the optimal Karhunen-Loeve Transform, given available partial boundary information, is well approximated by a close relative of the discrete sine transform (DST), with basis vectors that tend to vanish at the known boundary and maximize energy at the unknown boundary. The overall intraframe coding scheme thus switches between this variant of the DST named asymmetric DST (ADST), and traditional discrete cosine transform (DCT), depending on prediction direction and boundary information. The ADST is first compared with DCT in terms of coding gain under ideal model conditions and is demonstrated to provide significantly improved compression efficiency. The proposed adaptive prediction and transform scheme is then implemented within the H.264/AVC intra-mode framework and is experimentally shown to significantly outperform the standard intra coding mode. As an added benefit, it achieves substantial reduction in blocking artifacts due to the fact that the transform now adapts to the statistics of block edges. An integer version of this ADST is also proposed.     

基于人眼视觉特性的ROI渐进编码算法

一般基于感兴趣区域(ROI)的图像编码算法都没有充分考虑人眼视觉特性,在分析了JPEG2000中感兴趣区域编码的优缺点后,利用小波变换的特点并结合人眼视觉的掩蔽效应,提出了一种改进的ROI图像编码算法。首先将图像小波域中的所有低频系数进行移位处理,而对于小波域中的高频系数,仅对其属于ROI区域的系数进行移位处理,再利用等级树集合分割(SPIHT)算法进行编码传输。仿真实验证明了该算法比原有算法的图像主观质量更好。     

Motion compensated sequence coding using image pyramids

Image coding using image pyramids is a technique originally developed for still pictures. The authors report an image sequence coding technique with motion compensation using image pyramids, which gives greater data compression than conventional motion estimation algorithms.<>     

Region-based image coding using polynomial intensity functions

The vast majority of coded images are real-world images. These images consist of distinct objects within a scene, where each object has its own reflective, textural and lighting characteristics. Region-based image coding encodes these images by partitioning the scene into objects, and then describing each object's characteristics using a set of parameters. The paper uses orthonormal polynomial functions to describe the lighting and reflective characteristics of each object. The coefficients of these polynomials are coded with linear quantisers that have their decision boundaries spaced according to rate-distortion considerations. The textural component of each object is coded using vector quantisation of the autocorrelation coefficients of the residual. The partitioning of the image into distinct objects is achieved with a segmentation algorithm which attempts to maximise the rate-distortion performance of the encoding procedure as a whole. In doing so, the segmentation algorithm partitions the image into distinct objects as well as providing estimates for the optimal bit allocations among the polynomial coefficients. Results generated by this method show reconstructions with quality superior to other region-based methods, both objectively and subjectively     

Color image coding using morphological pyramid decomposition

Presents a new algorithm that utilizes mathematical morphology for pyramidal coding of color images. The authors obtain lossy color image compression by using block truncation coding at the pyramid levels to attain reduced data rates. The pyramid approach is attractive due to low computational complexity, simple parallel implementation, and the ability to produce acceptable color images at moderate data rates. In many applications, the progressive transmission capability of the algorithm is very useful. The authors show experimental results for color images at data rates of 1.89 bits/pixel.     

Wavelet-based image coding using nonlinear interpolative vectorquantization

We propose a reduced complexity wavelet-based image coding technique. Here, 64-D (for three stages of decomposition) vectors are formed by combining appropriate coefficients from the wavelet subimages, 16-D feature vectors are then extracted from the 64-D vectors on which vector quantization (VQ) is performed. At the decoder, 64-D vectors are reconstructed using a nonlinear interpolative technique. The proposed technique has a reduced complexity and has the potential to provide a superior coding performance when the codebook is generated using the training vectors drawn from similar images.     

Layered image coding using the DCT pyramid

A block-based subband image coder that exploits the ability to perform decimation in the discrete cosine transform (DCT) domain to effect a pyramidal data structure is described. The proposed "DCT pyramid" has a distinct feature of improved image rendition properties without the associated blocking artifacts at low bit-rates.     

Progressive image coding using trellis coded quantization

In this work, we present coding techniques that enable progressive transmission when trellis coded quantization (TCQ) is applied to wavelet coefficients. A method for approximately inverting TCQ in the absence of least significant bits is developed. Results are presented using different rate allocation strategies and different entropy coders. The proposed wavelet-TCQ coder yields excellent coding efficiency while supporting progressive modes analogous to those available in JPEG.