Subband Finite-State Vector Quantization for Still Image Coding

Subband coding (SBC) with vector quantization (VQ) has been shown to be an effective method for coding images at low bit rates. The basic idea of subband coding is to split up the frequency band of the signal and then to encode the subbands. Reconstruction is performed by decoding and merging the interpolated subband images. In VQ, the image to be encoded is first processed to yield a set of vectors. The input vectors are individually quantized to the closest codewords in the codebook. In this paper, we propose a new subband finite-state vector quantization (SBC-FSVQ) scheme that combines the SBC and the FSVQ. The frequency band decomposition of an image is carried out by means of 2D separable quadrature mirror filters (QMFs). In our coding scheme, we split the image spectrum into sixteen equally sized subbands. The FSVQ is used to improve the performance by using the correlations of the neighboring samples in the same subband. Thus, our SBC-FSVQ scheme not only has the advantages of the SBC-VQ scheme but also reduces the bit rate and improves the image quality. Experimental results are given and comparisons are made using our new schemes and some other coding techniques. Our technique yields good PSNR performance, for images both inside and outside a training set of five 512 × 512 images. In the experiments, it is found that our SBC-FSVQ scheme achieves the best PSNR performance at nearly the same bit rate.     

Adaptive channel error protection of subband encoded images

Protection of images that are encoded using subband coding from channel error is addressed. In this scheme the low-pass subband is encoded using DPCM (differential pulse-code modulation), and the other subbands are encoded using a scalar quantizer. The quantizers are all Lloyd-Max quantizers, from which the representation levels have fixed length codewords. First, considering only single errors in each codeword, a channel error distortion measure is derived for each quantizer, that is, for each subband. Codewords are assigned to the quantizer representation levels, yielding a low value of the distortion measure. Next, sets S_ij consisting of the jth bit from subband i are formed. Each set S _ij is assigned a particular BCH code C_ij. An algorithm that optimally assigns BCH codes C_ij to each set S_ij, based on a channel error distortion measure for the entire image, is derived. The protection scheme is adaptive, because each set of bits within each subband can be assigned a different error protection code. Examples show that this approach is preferable to assigning equal error protection codes to each set of bits. It is shown that in the case of a channel error probability of 10 ^-3, only 5% to 10% extra bits are needed for adequate channel error protection     

Orientation adaptive subband coding of images

In the subband coding of images, directionality of image features has thus far been exploited very little. The proposed subband coding scheme utilizes orientation of local image features to avoid the highly objectionable Gibbs-like phenomena observed at reconstructed image edges with conventional subband schemes at low bit rates, At comparable bit rates, the subjective image quality obtained by our orientation adaptive scheme is considerably enhanced over a conventional separable subband coding scheme, as well as other separable approaches such as the JPEG compression standard.     

Finite-state vector quantization by exploiting interband andintraband correlations for subband image coding

Subband coding (SBC) with vector quantization (VQ) has been shown to be an effective method for coding images at low bit rates. We split the image spectrum into seven nonuniform subbands. Threshold vector quantization (TVQ) and finite state vector quantization (FSVQ) methods are employed in coding the subband images by exploiting interband and intraband correlations. Our new SBC-FSVQ schemes have the advantages of the subband-VQ scheme while reducing the bit rate and improving the image quality. Experimental results are given and comparisons are made using our new scheme and some other coding techniques. In the experiments, it is found that SBC-FSVQ schemes achieve the best peak signal-to-noise ratio (PSNR) performance when compared to other methods at the same bit rate.     

一种综合源编码和信道编码的图像编码方案

提出了一新的综合源编码和信道编码的图像编码传输方案，对子波变换后各个子带采用基于统计特性的变系数定长（VCFL）编码后选择不同码率的RCPC（码率兼容的删除卷积码，Rate Compatible Punctured Convolutional code)信道编码以提供不同程度的差错保护（UEP）并进行传输。在给定传输的总比特数的情况下，通过一种优化算法使方案的总体失真最小。模拟结果表明新方案压缩比高，在较高的传输误码率情况下，表现出良好的抗误码能力。     

Subband coding of images using vector quantization

A novel two-dimensional subband coding technique is presented that can be applied to images as well as speech. A frequency-band decomposition of the image is carried out by means of 2D separable quadrature mirror filters, which split the image spectrum into 16 equal-rate subbands. These 16 parallel subband signals are regarded as a 16-dimensional vector source and coded as such using vector quantization. In the asymptotic case of high bit rates, a theoretical analysis yields that a lower bound to the gain is attainable by choosing this approach over scalar quantization of each subband with an optimal bit allocation. It is shown that vector quantization in this scheme has several advantages over coding the subbands separately. Experimental results are given, and it is shown the scheme has a performance that is comparable to that of more complex coding techniques     

Improved moment preserving block truncation coding for image compression

A novel image compression scheme based on moment preserving block truncation coding (MPBTC) is introduced. To reduce the bit rate of the traditional MPBTC scheme, the block search order coding technique is employed to exploit the similarity among neighbouring image blocks. In addition, smooth blocks and complex blocks are processed using different methods. Experimental results show that the proposed scheme provides good image quality at a low bit rate.     

Wavelet packets and spatial adaptive intraband coding of images

In this work, we present a coding scheme based on a rate-distortion optimum wavelet packets decomposition and on an adaptive coding procedure that exploits spatial non-stationarity within each subband. We show, by means of a generalization of the concept of coding gain to the case of non-stationary signals, that it may be convenient to perform subband decomposition optimization in conjunction with intraband optimal bit allocation. In our implementation, each subband is partitioned into blocks of coefficients that are coded using a geometric vector quantizer with a rate determined on the basis of spatially local statistical characteristics. The proposed scheme appears to be simpler than other wavelet packets-based schemes presented in the literature and achieves good results in terms of both compression and visual quality.     

Wavelet image coding using variable blocksize vector quantization with optimal quadtree segmentation

In this paper, we propose an image coding scheme by using the variable blocksize vector quantization (VBVQ) to compress wavelet coefficients of an image. The scheme is capable of finding an optimal quadtree segmentation of wavelet coefficients of an image for VBVQ subject to a given bit budget, such that the total distortion of quantized wavelet coefficients is minimal. From our simulation results, we can see that our proposed coding scheme has higher performance in PSNR than other wavelet/VQ or subband/VQ coding schemes.     

Embedded image coding using zerotrees of wavelet coefficients

The embedded zerotree wavelet algorithm (EZW) is a simple, yet remarkably effective, image compression algorithm, having the property that the bits in the bit stream are generated in order of importance, yielding a fully embedded code. The embedded code represents a sequence of binary decisions that distinguish an image from the “null” image. Using an embedded coding algorithm, an encoder can terminate the encoding at any point thereby allowing a target rate or target distortion metric to be met exactly. Also, given a bit stream, the decoder can cease decoding at any point in the bit stream and still produce exactly the same image that would have been encoded at the bit rate corresponding to the truncated bit stream. In addition to producing a fully embedded bit stream, the EZW consistently produces compression results that are competitive with virtually all known compression algorithms on standard test images. Yet this performance is achieved with a technique that requires absolutely no training, no pre-stored tables or codebooks, and requires no prior knowledge of the image source. The EZW algorithm is based on four key concepts: (1) a discrete wavelet transform or hierarchical subband decomposition, (2) prediction of the absence of significant information across scales by exploiting the self-similarity inherent in images, (3) entropy-coded successive-approximation quantization, and (4) universal lossless data compression which is achieved via adaptive arithmetic coding     

Region adaptive subband image coding

We present a region adaptive subband image coding scheme using the statistical properties of image subbands for various subband decompositions. Motivated by analytical results obtained when the input signal to the subband decomposition is a unit step function, we analyze the energy packing properties toward the lower frequency subbands, edges, and the dependency of energy distribution on the orientation of the edges, in subband decomposed images. Based on these investigations and ideal analysis/synthesis filtering done in the frequency domain, the region adaptive subband image coding scheme extracts suitably shaped regions in each subband and then uses adaptive entropy-constrained quantizers for different regions under the assumption of a generalized Gaussian distribution for the image subbands. We also address the problem of determining an optimal subband decomposition among all possible decompositions. Experimental results show that visual degradations in the reconstructed image are negligible at a bit rate of 1.0 b/pel and reasonable quality images are obtainable at rates as low as 0.25 b/pel.     

Space-frequency localized image compression

Subband and wavelet-based image compression can be viewed as frequency oriented techniques because each subimage in the decomposition is essentially a band-pass version of the original image. The authors suggest a space-frequency partition scheme to fully exploit the excellent localization properties of wavelets in both the spatial and frequency domains. Due to the relatively large number of blocks in this partition compared with traditional subband coders, the rate required for communicating the quantizer configurations must be taken into account. An iterative bit allocation algorithm is suggested that minimizes the mean square error given the overall rate for specifying the quantization configuration and for quantizing the wavelet coefficients. Images encoded using scalar quantization under this scheme show improvements in PSNR versus rate over traditional subband and wavelet-based methods.     

Unequal error protection for MPEG-2 video transmission over wireless channels

This paper proposes an unequal error protection (UEP) method for MPEG-2 video transmission. Since the source and channel coders are normally concatenated, if the channel is noisy, more bits are allocated to channel coding and fewer to source coding. The situation is reversed when the channel conditions are more benign. Most of the joint source channel coding (JSCC) methods assume that the video source is subband coded, the bit error sensitivity of the source code can be modeled, and the bit allocations for different subband channels will be calculated. The UEP applied to different subbands is the rate compatible punctured convolution channel coder. However, the MPEG-2 coding is not a subband coding, the bit error sensitivity function for the coded video can no longer be applied. Here, we develop a different method to find the rate-distortion functions for JSCC of the MPEG-2 video. In the experiments, we show that the end-to-end distortion of our UEP method is smaller than the equal error protection method for the same total bit-rate.     

A motion compensated subband coder for very low bit-rates

A motion compensated subband coder with block-based processing for very low bit-rate video coding is presented. The motion compensated prediction is realized by using overlapping blocks. A forward analysis is introduced to select the blocks to be updated. In contrast to the conventional subband coding which is applied to the whole image, the subband coding here is applied to selected blocks only. In order to reduce the number of samples to be coded, a symmetric-periodic extension technique is applied in each stage of the subband analysis and synthesis filtering. A psychovisual model of the human visual perception is used to control the bit allocation and the adaptive quantization. Experimental results obtained with the presented coder at transmission bit-rates of 8, 16 and 24 kbit/s are presented. A comparison of the presented coder with ITU-T TMN-3 coder shows, that a PSNR gain of about 2.0 dB is achieved for typical videophone sequences with head and shoulder scenes.     

Adaptive edge-based side-match finite-state classified vectorquantization with quadtree map

Vector quantization (VQ) is an effective image coding technique at low bit rate. The side-match finite-state vector quantizer (SMVQ) exploits the correlations between neighboring blocks (vectors) to avoid large gray level transition across block boundaries. A new adaptive edge-based side-match finite-state classified vector quantizer (classified FSVQ) with a quadtree map has been proposed. In classified FSVQ, blocks are arranged into two main classes, edge blocks and nonedge blocks, to avoid selecting a wrong state codebook for an input block. In order to improve the image quality, edge vectors are reclassified into 16 classes. Each class uses a master codebook that is different from the codebooks of other classes. In our experiments, results are given and comparisons are made between the new scheme and ordinary SMVQ and VQ coding techniques. As is shown, the improvement over ordinary SMVQ is up to 1.16 dB at nearly the same bit rate, moreover, the improvement over ordinary VQ can be up to 2.08 dB at the same bit rate for the image, Lena. Further, block boundaries and edge degradation are less visible because of the edge-vector classification. Hence, the perceptual image quality of classified FSVQ is better than that of ordinary SMVQ.     

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。     

H.264中率失真代价估计模型研究

提出了一种新的率失真代价估计模型。首先为提供更加精确的帧内/帧间宏块的编码比特数的估算,提出了一种新的码率估计模型,该码值为一序列编码参数的线性组合,这些参数跟熵编码和变换系数相关,从而得出新的性能更加优越的率失真代价估计模型。最后在率失真代价估计模型的效果分析、性能分析等多个方面进行详细的分析测试。实验结果表明,该模型在保证PSNR和码长变化不大的情况下大大地加快了编码速度。     

图像的空间可分级压缩编码及其码率分配

为了能使图像压缩编码算法同时具有较高的压缩率和良好的压缩性能,分析了SPIHT算法,在相同压缩效率的情况下,将其进一步改进,使之具有空间可分级性。在编码过程中,单个像素的相关信息按其所在的分辨率层输出到基础层或增强层码流中,而对于集合的测试信息按其最高层像素所在的分辨率层以较大的概率输出到相应的码流中。这样,虽然低频子带与高频子带相关联而编码,但实验结果显示与低频子带单独编码的性能非常接近。同时给出了一种基础层和增强层间的码率分配方案。实际结果显示：随码率的增大,基础层所占的比率越来越低;对包含边缘较多的图像,其基础层码率所占的比率也较低。     

Color image compression by moment-preserving and block truncationcoding techniques

A new color image compression technique based on moment-preserving and block truncation coding is proposed. An input image is divided into nonoverlapping blocks and each block pixel is assigned one of two representative colors, which are computed with analytic formulas derived from preserving certain moments in the block. A bit map is then generated for each block to represent the pixels' colors. Different uniformity conditions in the representative colors are also identified and utilized to save code bits. Good average compression ratios up to about 13 can be achieved, as shown by experimental results     

一种改进的相关图像矢量量化编码算法

本文提出了一种改进的图像矢量量化编码算法。该算法通过采用增加预测块，以及根据相邻块状态进行控制信息的条件熵编码等改进方法，进一步提高了算法的编码效率，为了便于算法实现，本文对图像的边缘引进的一致的处理方法。测试结果表明，相对于无记忆适量量化编码算法，比特率约下降４０％，相对于文献［５］算法，比特率约下降１５％。