Edge-based motion compensated classified DCT with quadtree for image sequence coding

The motion compensated discrete cosine transform coding (MCDCT) is an efficient image sequence coding technique. In order to further reduce the bit-rate for the quantizied DCT coefficients and keep the visual quality, we propose an adaptive edge-based quadtree motion compensated discrete cosine transform coding (EQDCT). In our proposed algorithm, the overhead moving information is encoded by a quadtree structure and the nonedge blocks will be encoded at lower bit-rate but the edge blocks will be encoded at higher bit-rate. The edge blocks will be further classified into four different classes according to the orientations and locations of the edges. Each class of edge blocks selects the different set of the DCT coefficients to be encoded. By this method, we can just preserve and encode a few DCT coefficients, but still maintain the visual quality of the images. In the proposed EQDCT image sequence coding scheme, the average bit-rate of each frame is reduced to 0.072 bit/pixel and the average PSNR value is 32.11 dB.     

基于二维APDCSF的列率子带特征编码方法

提出了一种子带编码的新方法。该方法利用二维全相位离散反余弦列率滤波器（APDCSF）对图像进行子带分解;对于低频子带图像采用直接斜交多重亚采样和基于全相位离散反余弦列牢滤波器（APDICsF）的多重旋转内插恢复．而对高频子带图像利用直方图自动阈值化提取如边缘和线等特征的图像元;根据各个子带的图像元的特征分别进行编码压缩,解压缩后利用凸集投影重建原始图像。该方法消除了传统的离散余弦变换（DCT）编码的方块化效应,与基于小波变换的子带特征编码方法相比,计算复杂度小,压缩率高,主观视觉性能好,对于灰阶图像可达到0．1～0．3bpp,特别适用于低比特率图像压缩。     

All phase biorthogonal transform and its application in JPEG-like image compression

This paper proposes new concepts of the all phase biorthogonal transform (APBT) and the dual biorthogonal basis vectors. In the light of all phase digital filtering theory, three kinds of all phase biorthogonal transforms based on the Walsh transform (WT), the discrete cosine transform (DCT) and the inverse discrete cosine transform (IDCT) are proposed. The matrices of APBT based on WT, DCT and IDCT are deduced, which can be used in image compression instead of the conventional DCT. Compared with DCT-based JPEG (DCT-JPEG) image compression algorithm at the same bit rates, the PSNR and visual quality of the reconstructed images using these transforms are approximate to DCT, outgoing DCT-JPEG at low bit rates especially. But the advantage is that the quantization table is simplified and the transform coefficients can be quantized uniformly. Therefore, the computing time becomes shorter and the hardware implementation easier.     

Rate bounds on SSIM index of quantized images

In this paper, we derive bounds on the structural similarity (SSIM) index as a function of quantization rate for fixed-rate uniform quantization of image discrete cosine transform (DCT) coefficients under the high-rate assumption. The space domain SSIM index is first expressed in terms of the DCT coefficients of the space domain vectors. The transform domain SSIM index is then used to derive bounds on the average SSIM index as a function of quantization rate for uniform, Gaussian, and Laplacian sources. As an illustrative example, uniform quantization of the DCT coefficients of natural images is considered. We show that the SSIM index between the reference and quantized images fall within the bounds for a large set of natural images. Further, we show using a simple example that the proposed bounds could be very useful for rate allocation problems in practical image and video coding applications.     

A combined-transform coding (CTC) scheme for medical images

A combined-transform coding (CTC) scheme is proposed to reduce the blocking artifact of conventional block transform coding and hence to improve the subjective performance. The proposed CTC scheme is described and its information-theoretic properties are investigated. Computer simulation results for a class of chest X-ray images are presented. A comparison between the CTC scheme and the conventional discrete cosine transform (DCT) and discrete Walsh-Hadamard transform (DWHT) demonstrates the performance improvement of the proposed scheme. In addition, combined coding can also be used in noiseless coding, yielding a slight improvement in the compression performance if it is used properly.     

Postprocessing of low bit-rate block DCT coded images based on a fields of experts prior.

Transform coding using the discrete cosine transform (DCT) has been widely used in image and video coding standards, but at low bit rates, the coded images suffer from severe visual distortions which prevent further bit reduction. Postprocessing can reduce these distortions and alleviate the conflict between bit rate reduction and quality preservation. Viewing postprocessing as an inverse problem, we propose to solve it by the maximum a posteriori criterion. The distortion caused by coding is modeled as additive, spatially correlated Gaussian noise, while the original image is modeled as a high order Markov random field based on the fields of experts framework. Experimental results show that the proposed method, in most cases, achieves higher PSNR gain than other methods and the processed images possess good visual quality. In addition, we examine the noise model used and its parameter setting. The noise model assumes that the DCT coefficients and their quantization errors are independent. This assumption is no longer valid when the coefficients are truncated. We explain how this problem can be rectified using the current parameter setting.     

Improvements of Transform Coding Algorithm for Motion-Compensated Interframe Prediction Errors-DCT/SQ Coding

A new hybrid coding method for transmitting videoconferencing images at a bit rate 384 kbits/s is proposed. Considering the characteristics of motion-compensated interframe prediction errors for typical videoconferencing scenes, a filter is introduced to separate pulsive components on which conventional discrete cosine transform (DCT) coding method does not work well. These separated pulsive components are coded by using scalar quantization (SQ). The remainder are DCT coded. For DCT coefficients, an adaptive coding method based on the classification of DCT coefficients is applied in order to improve the coding performance. Since the proposed method employs both DCT coding and SQ of prediction errors, it is named "DCT/SQ coding method." Experimental results show that the DCT/SQ coding method is effective to reduce so-called mosquito effects, and thus it can improve the quality of decoded images.     

Block-based frequency scalable technique for efficient hierarchical coding

In this paper, we propose a block-based frequency scalable technique for efficient hierarchical coding. The proposed technique divides an image into its multiple resolution versions, based on the spectral properties of discrete cosine transform (DCT) kernels. We present that spectral decomposition, downsampling, and DCT operations are performed effectively over input DCT coefficients of one-dimensional (1-D) and two-dimensional (2-D) signals by using the proposed transform matrices. The proposed image coder is observed to reduce the computational complexity and the memory buffer size with a higher peak signal-to-noise ratio (PSNR), when compared with the traditional hierarchical image coder. In addition, the proposed architecture can preserve compatibility easily with the previous DCT-based image coder.     

Multispectral code excited linear prediction coding and itsapplication in magnetic resonance images

This paper reports a multispectral code excited linear prediction (MCELP) method for the compression of multispectral images. Different linear prediction models and adaptation schemes have been compared. The method that uses a forward adaptive autoregressive (AR) model has been proven to achieve a good compromise between performance, complexity, and robustness. This approach is referred to as the MFCELP method. Given a set of multispectral images, the linear predictive coefficients are updated over nonoverlapping three-dimensional (3-D) macroblocks. Each macroblock is further divided into several 3-D micro-blocks, and the best excitation signal for each microblock is determined through an analysis-by-synthesis procedure. The MFCELP method has been applied to multispectral magnetic resonance (MR) images. To satisfy the high quality requirement for medical images, the error between the original image set and the synthesized one is further specified using a vector quantizer. This method has been applied to images from 26 clinical MR neuro studies (20 slices/study, three spectral bands/slice, 256x256 pixels/band, 12 b/pixel). The MFCELP method provides a significant visual improvement over the discrete cosine transform (DCT) based Joint Photographers Expert Group (JPEG) method, the wavelet transform based embedded zero-tree wavelet (EZW) coding method, and the vector tree (VT) coding method, as well as the multispectral segmented autoregressive moving average (MSARMA) method we developed previously.     

The Effectiveness and Efficiency of Hybrid Transform/DPCM Interframe Image Coding

We seek to evaluate the efficiency of hybrid transform/ DPCM interframe image coding relative to an optimal scheme that minimizes the mean-squared error in encoding a stationary Gaussian image sequence. The stationary assumption leads us to use the asymptotically optimal discrete Fourier transform (DFT) on the full frame of an image. We encode an actual image sequence with full-frame DFT/DPCM at several rates and compare it to previous interframe coding results with the same sequence. We also encode a single frame at these same rates using a full-frame DFT to demonstrate the inherent coding gains of interframe transform DPCM over intraframe coding. We then generate a pseudorandom image sequence with precise Gauss-Markov statistics and encode it by hybrid full-frame DFT/DPCM at various rates. We compare the signal-to-noise ratios (SNR's) of these reconstructions to the optimal ones calculated from the rate-distortion function. We conclude that in a medium rate range below 1 bit/pel/frame where reconstructions for hybrid transform/ DPCM may be unsatisfactory, there is enough margin for improvement to consider more sophisticated coding schemes.     

Human visual weighted progressive image transmission

A progressive image transmission scheme which combines transform coding with the human visual system (HVS) model is developed. The adaptive transform coding of W.H. Chen and C.H. Smith (1977) is utilized to classify an image into four equally populated subblocks based on their AC energies. The modulation transfer function (MTF) of the HVS model is obtained experimentally, based on processing a number of test images. A simplified technique for incorporating the MTF into the discrete cosine transform (DCT) domain is utilized. In the hierarchical image buildup, the image is first reconstructed from the DC coefficients of all subblocks. Further transmission hierarchy of transform coefficients and consequent image buildup are dependent on their HVS weighted variances. The HVS weighted reconstructed images are compared to the ones without any weighting at several stages. The HVS weighted progressive image transmission results in perceptually higher quality images compared to the unweighted scheme     

An adaptive 3-D discrete cosine transform coder for medical imagecompression

A new three-dimensional (3-D) discrete cosine transform (DCT) coder for medical images is presented. In the proposed method, a segmentation technique based on the local energy magnitude is used to segment subblocks of the image into different energy levels. Then, those subblocks with the same energy level are gathered to form a 3-D cuboid. Finally, 3-D DCT is employed to compress the 3-D cuboid individually. Simulation results show that the reconstructed images achieve a bit rate lower than 0.25 bit per pixel even when the compression ratios are higher than 35. As compared with the results by JPEG and other strategies, it is found that the proposed method achieves better qualities of decoded images     

On the adaptive three-dimensional transform coding techniques for moving images

In this paper, an adaptive three-dimensional transform coding technique based on the 3-D discrete cosine transform (DCT) for removing the temporal correlation is proposed. Because of the nonstationary nature of the image data, the energy distribution in a 3-D DCT block varies along the vertical, horizontal and temporal directions. Thus, adaptive schemes, such as the 3-D classification, the classified linear scanning technique and the VLC table selection scheme, are used to take local variations into account. Also, in our approach, a hybrid technique, which adaptively combines relatively simple inter-frame coding with intra-frame coding, is presented. Through intensive computer simulations, the performance of the proposed 3-D transform coding technique is evaluated on several well-known moving sequences. The results show that, especially for moving sequences containing slow or moderate motion, the proposed technique provides an improved performance over the scheme with motion compensation (CCITT, 1989) at rates above 0.5 b/pixel (bpp), and a good visual quality of the reconstructed images is also obtained. Thus, the proposed 3-D transform coding technique is believed to be a good candidate for the digital VCR, since motion compensation is not required in the proposed 3-D coding technique.     

A new texture generation method based on pseudo-DCT coefficients.

In this paper, a new method for generating different texture images is presented. This method involves a simple transform from a certain one-dimensional (1-D) signal to an expected two-dimensional (2-D) image. Unlike traditional methods, the input signal is generated by a simple 1-D function in our work instead of a sample texture. We first transform the 1-D input signal into frequency domain using fast Fourier transform. Based on the sufficient analysis in 2-D discrete cosine transform (DCT) domain, where each of the coefficients expresses a texture feature in a certain direction, the 2-D pseudo-DCT coefficients are then constructed by appropriately rearranging the Fourier coefficients in terms of their frequency components. Finally, the corresponding texture image can be produced by 2-D inverse DCT algorithm. We applied the proposed method to generate several stochastic textures (i.e., cloud, illumination, and sand), and several structural texture images. Experimental results indicate the good performance of the proposed method.     

Block classification for an adaptive 1-D/2-D DCT video coding

A classification scheme for an adaptive one- or two-dimensional discrete cosine transform (1-D/2-D DCT) technique is described and demonstrated to be a more appropriate strategy than the conventional 2-D DCT for coding motion compensated prediction error images. Two block-based classification methods are introduced and their accuracy in predicting the correct transform type discussed. The accuracy is assessed with a classification measure designed to ascertain the effectiveness of energy compaction when the predicted transform class is applied; vis-a-vis horizontally, vertically or two-dimensionally transformed blocks. Energy compaction is a useful property not only for efficient entropy coding but also for enhancing the resilience of the transform coder to quantisation noise. Improvements against the homogeneous 2-D DCT system both in terms of the peak signal to noise ratio and subjective assessments are achieved. Observable ringing artifacts along edges, which are usual in conventional transform coding, are reduced     

DCT/DST alternate-transform image coding

An image coding method for low bit rates is proposed. It is based on alternate use of the discrete cosine transform (DCT) and the discrete sine transform (DST) on image blocks. This procedure achieves the removal of redundancies in the correlation between neighboring blocks as well as the preservation of continuity across the block boundaries. An outline of the mathematical justification of the method, assuming a certain first-order Gauss-Markov model, is given. The resulting coding method is then adapted to nonstationary real images by locally adapting the model parameters and improving the block classification technique. Simulation results are shown and compared with the performance of related previous methods, namely adaptive DCT and fast Karhunen-Loeve transform (FKLT)     

Distributions of the Two-Dimensional DCT Coefficients for Images

For a two-dimensional discrete cosine transform (DCT) image coding system, there have been different assumptions concerning the distributions of the transform coefficients. This paper presents results of distribution tests that indicate that for many images the statistics of the coefficients are best approximated by a Gaussian distribution for the DC coefficient and a Laplacian distribution for the other coefficients. Furthermore, from a simulation of the DCT coding System it is shown that the assumption that the coefficients are Laplacian yields a higher actual output signal-to-noise ratio and a much better agreement between theory and simulation than the Gaussian assumption.     

Prioritized DCT for compression and progressive transmission ofimages

An approach is based on the block discrete cosine transform (DCT). The novelty of this approach is that the transform coefficients of all image blocks are coded and transmitted in absolute magnitude order. The resulting ordered-by-magnitude transmission is accomplished without sacrificing coding efficiency by using partition priority coding. Coding and transmission are adaptive to the characteristics of each individual image. and therefore, very efficient. Another advantage of this approach is its high progression effectiveness. Since the largest transform coefficients that capture the most important characteristics of images are coded and transmitted first, this method is well suited for progressive image transmission. Further compression of the image-data is achieved by multiple distribution entropy coding, a technique based on arithmetic coding. Experiments show that the approach compares favorably with previously reported DCT and subband image codecs.     

Transform methods for seismic data compression

The authors consider the development and evaluation of transform coding algorithms for the storage of seismic signals. Transform coding algorithms are developed using the discrete Fourier transform (DFT), the discrete cosine transform (DCT), the Walsh-Hadamard transform (WHT), and the Karhunen-Loeve transform (KLT). These are evaluated and compared to a linear predictive coding algorithm for data rates ranging from 150 to 550 bit/s. The results reveal that sinusoidal transforms are well-suited for robust, low-rate seismic signal representation. In particular, it is shown that a DCT coding scheme reproduces faithfully the seismic waveform at approximately one-third of the original rate     

An Analysis of Error Behavior in the Implementation of 2-D Orthogonal Transformations

The paper analyzes the effect of finite-length arithmetic in the calculation of 2-D linear transformations employed in some picture coding algorithms. Since the condition of zero-error in general direct and reverse transformations leads to results of little practical importance, an analysis is carried out on the statistical properties of error in 2-D linear transformation with given length of arithmetics. Then the important case of discrete cosine transform (DCT) applied to real images is considered in detail. The results of the paper allow a circuit designer to determine the representation accuracy of the one- and two-dimensional coefficients required to satisfy a preassigned reconstruction error on the image.