基于全相位反余弦双正交变换的JPEG图像压缩技术

提出了一种新型的基于全相位反余弦双正交变换(APIDCBT)的JPEG图像压缩技术,APIDCBT矩阵是一种新型的变换矩阵,给出它的具体形式,提出了双正交变换与对偶双正交基向量的概念.通过与传统的离散余弦变换(DCT)进行比较,表明了APIDCBT算法可以不用量化表,节省运算时间,与DCT可达到同样的压缩效果,并且在低码率情况下优于DCT.     

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。     

Image coding using lapped biorthogonal transform

The wireless sensor network utilizes image compression algorithms like JPEG, JPEG2000, and SPIHT for image transmission with high coding efficiency. During compression, discrete cosine transform (DCT)–based JPEG has blocking artifacts at low bit-rates. But this effect is reduced by discrete wavelet transform (DWT)–based JPEG2000 and SPIHT algorithm but it possess high computational complexity. This paper proposes an efficient lapped biorthogonal transform (LBT)–based low-complexity zerotree codec (LZC), an entropy coder for image coding algorithm to achieve high compression. The LBT-LZC algorithm yields high compression, better visual quality with low computational complexity. The performance of the proposed method is compared with other popular coding schemes based on LBT, DCT and wavelet transforms. The simulation results reveal that the proposed algorithm reduces the blocking artifacts and achieves high compression. Besides, it is analyzed for noise resilience.     

全相位沃尔什双正交变换及其在图像压缩中的应用

本文提出了全相位沃尔什双正交变换和对偶双正交基向量的新概念,并提出了一种基于这种变换的、新的图像压缩算法.与JPEG压缩编码算法中的DCT变换做比较,在相同码率下,采用全相位沃尔什双正交变换的重建图像峰值信噪比与DCT变换的大致相同,而该方法最大的优点是量化简单,能对变换系数进行均一量化,从而大大缩短运算时间,且便于硬件实现.     

New family of lapped biorthogonal transform via lifting steps

By scaling all discrete cosine transform (DCT) intermediate output coefficients of the lapped transform and employing the type-II and type-IV DCT based on lifting steps, a new family of lapped biorthogonal transform is introduced, called the IntLBT. When all the elements with a floating point of each lifting matrix in the IntLBT are approximated by binary fractions, the IntLBT is implemented by a series of dyadic lifting steps and provides very fast, efficient in-place computation of the transform coefficients, and all internal nodes have finite precision. When each lifting step in the IntLBT is implemented using the same nonlinear operations as those used in the well known integer-to-integer wavelet transform, the IntLBT maps integers to integers, so it can express lossless image information. As an application of the novel IntLBT to lossy image compression, simulation results demonstrate that the IntLBT has significantly less blocking artefacts, higher peak signal-to-noise ratio, and better visual quality than the DCT. More importantly, the IntLBT's coding performance is approximately the same as that of the much more complex Cohen-Daubechies-Feauveau (CDF) 9/7-tap biorthogonal wavelet with floating-point coefficients, and in some cases even surpasses that of the CDF 9/7-tap biorthogonal wavelet.     

Low-error carry-free fixed-width multipliers with low-cost compensation circuits

In this paper, we propose a low-error fixed-width redundant multiplier design. The design is based on the statistical analysis of the error compensation value of the truncated partial products in binary signed-digit representation with modified Booth encoding. The overall truncation error is significantly reduced compared with other previous approaches. Furthermore, the derived relationship between the compensation value and the truncated digits is so simple that the area cost of the corresponding compensation circuit is almost negligible. The fixed-width multiplier design is also applied to the discrete cosine transform/inverse discrete cosine transform (DCT/IDCT) computation in JPEG image compression.     

Direct recursive structures for computing radix-r two-dimensional DCT/IDCT/DST/IDST

In this paper, new recursive structures for computing radix-r two-dimensional (2-D) discrete cosine transform (DCT) and 2-D inverse DCT (IDCT) are proposed. The 2-D DCT/IDCT are first decomposed into cosine-cosine and sine-sine transforms. Based on indexes of transform bases, the regular pre-addition preprocess is established and the recursive structures for 2-D DCT/IDCT, which can be realized in a second-order infinite-impulse response (IIR) filter, are derived without involving any transposition procedure. For computation of 2-D DCT/IDCT, the recursive loops of the proposed structures are less than that of one-dimensional DCT/IDCT recursive structures, which require data transposition to achieve the so-called row-column approach. With advantages of fewer recursive loops and no transposition, the proposed recursive structures achieve more accurate results and less power consumption than the existed methods. The regular and modular properties are suitable for very large-scale integration (VLSI) implementation. By using similar procedures, the recursive structures for 2-D DST and 2-D IDST are also proposed.     

Statistical distributions of DCT coefficients and their application to an interframe compression algorithm for 3-D medical images

Displacement estimated interframe (DEI) coding, a coding scheme for 3-D medical image data sets such as X-ray computed tomography (CT) or magnetic resonance (MR) images, is presented. To take advantage of the correlation between contiguous slices, a displacement-compensated difference image based on the previous image is encoded. The best fitting distribution functions for the discrete cosine transform (DCT) coefficients obtained from displacement compensated difference images are determined and used in allocating bits and optimizing quantizers for the coefficients. The DEI scheme is compared with 2-D block discrete cosine transform (DCT) as well as a full-frame DCT using the bit allocation technique of S. Lo and H.K. Huang (1985). For X-ray CT head images, the present bit allocation and quantizer design, using an appropriate distribution model, resulted in a 13-dB improvement in the SNR compared to the full-frame DCT using the bit allocation technique. For an image set with 5-mm slice thickness, the DEI method gave about 5% improvement in the compression ratio on average and less blockiness at the same distortion. The performance gain increases to about 10% when the slice thickness decreases to 3 mm.     

Arbitrary resizing of images in DCT domain using lapped transforms

An arbitrary L/M-fold image resizing method using lapped transforms is presented. The resizing operation is carried out in the lapped transform domain, by converting the images in the discrete cosine transform (DCT) domain into those in the lapped transform domain and vice versa. The proposed method provides visually fine images, while reducing the blocking effect to a very low level for images compressed at low bit rates.     

基于改进DA算法的2—D IDCT系统设计

离散余弦变换已成为图像压缩中一标准技术,本文给出了基于DA算法的二维离散余弦逆变换（2－DIDCT）系统的设计。在设计过程中根据实际情况提出了一种改进算法,通过采用此改进DA算法,整个2－DIDCT系统在提高速度的同时可大大减少面积。设计采用自顶向下设计方法,用VHDL进行描述,整个系统在SYMOPSYS工具上进行设计及仿真,最终综合到门级电路。     

基于离散分数阶角变换与关联混沌映射的双图像加密算法

为了实现对两个明文进行同步安全加密,提出了联合离散多参数分数阶角变换与低维映射的双图像加密算法.基于离散余弦变换(DCT)与Zigzag扫描建立了复合系数矩阵模型,通过反离散余弦变换(IDCT)将两个明文融合成一幅图像;通过耦合Logistic映射,利用明文像素均值与外部密钥计算其初始条件值,并迭代该耦合映射,输出2个随机序列;分别对这2个随机序列进行排序,设计位置数组扰乱机制对复合明文进行置乱;将置乱密文分解为2个新分量,利用Logistic映射与初始明文分别生成混沌随机与调制相位掩码,将2个新分量融合成临时密文;基于离散分数角变换构建了新的2D多参数分数阶角变换,设计加密模型并完成图像加密.结果表明,与已有双图像加密机制相比所提算法的保密性更佳,有更好的抗明文攻击特性.     

A new algorithm to compute the DCT and its inverse

A novel algorithm to convert the discrete cosine transform (DCT) to skew-circular convolutions is presented. The motivation for developing such an algorithm is the fact that VLSI implementation of distributed arithmetic is very efficient for computing convolutions. It is also shown that the inverse DCT (IDCT) can be computed using the same building blocks which are used for computing the DCT. A DCT/IDCT processor can be designed to compute either the DCT or the IDCT depending on a 1-b control signal     

Algorithm-based low-power transform coding architectures: themultirate approach

In most low-power VLSI designs, the supply voltage is usually reduced to lower the total power consumption. However, the device speed will be degraded as the supply voltage goes down. In this paper, we propose new algorithmic-level techniques to compensate the increased delays based on the multirate approach. We apply the technique of polyphase decomposition to design low-power transform coding architectures, in which the transform coefficients are computed through decimated low-speed input sequences. Since the operating frequency is M-times slower than the original design while the system throughput rate is still maintained, the speed penalty can be compensated at the architectural level. We start with the design of low-power multirate discrete cosine transform (DCT)/inverse discrete cosine transform (IDCT) VLSI architectures. Then the multirate low-power design is extended to the modulated lapped transform (MLT), extended lapped transform (ELT), and a unified low-power transform coding architecture. Finally, we perform finite-precision analysis for the multirate DCT architectures. The analytical results can help us to choose the optimal wordlength for each DCT channel under required signal-to-noise ratio (SNR) constraint, which can further reduce the power consumption at the circuit level. The proposed multirate architectures can also be applied to very high-speed block discrete transforms in which only low-speed operators are required     

A new IDCT-DFT relationship reducing the IDCT computational cost

This paper reconsiders the discrete cosine transform (DCT) algorithm of Narashima and Peterson (1978) in order to reduce the computational cost of the evaluation of N-point inverse discrete cosine transform (IDCT) through an N-point FFT. A new relationship between the IDCT and the discrete Fourier transform (DFT) is established. It allows the evaluation of two simultaneous N-point IDCTs by computing a single FFT of the same dimension. This IDCT implementation technique reduces by half the number of operations     

A 110-K transistor 25-MPixels/s configurable image transformprocessor unit

A configurable architecture for performing image transform algorithms is presented that provides a better tradeoff between low complexity and algorithm flexibility than either software-programmable processors or dedicated ASIC's. The configurable processor unit requires only 110 K transistors and can execute several image transform algorithms. By emulating the signal flow of the algorithms in hardware, rather than software, complexity is reduced by an order of magnitude compared with current software programmable video signal processors, while providing more flexibility than single function ASIC's. The processor has been fabricated in 1.2-μm CMOS and has been successfully used to execute the discrete cosine transform/inverse discrete cosine transform (DCT/IDCT), subband coding, vector quantization, and two-dimensional filtering algorithms at pixel rates up to 25 MPixels/s     

An Efficient IDCT Processor Design for HDTV Applications

This paper proposes a high performance and low cost inverse discrete cosine transform (IDCT) processor for high definition Television (HDTV) applications by using cyclic convolution and hardwired multipliers. By properly arranging the input sequence, we formulate the one-dimensional (1-D) IDCT into cyclic convolution that is regular and suitable for VLSI implementation. The hardwired multiplier that implements multiplication with IDCT coefficients are first scaled and optimized by using the common sub-expression techniques. Based on these techniques, the data-path in the proposed two-dimensional (2-D) IDCT design costs 7504 gates plus 1024 bits of memory with 100 M pixels/sec throughput according to the cost estimation based on the cell library of COMPASS 0.6 m SPDM CMOS technology. Also, we have verified that the precision analysis of the proposed 2-D 8 × 8 IDCT meets the demands of IEEE Std. 1180-1990. Due to the good performance in the computing speed as well as the hardware cost, the proposed design is compact and suitable for HDTV applications. This design methodology can be applied to forward DCT as well as other transforms like discrete sine transform (DST), discrete Fourier transform (DFT), and discrete Hartley transform (DHT).     

Condensed recursive structures for computing multidimensional DCT/IDCT with arbitrary length

In this paper, efficient recursive structures for computing arbitrary length M-dimensional (M-D) discrete cosine transform (DCT) and its inverse DCT (IDCT) are proposed. The M-D DCT and IDCT are first converted into condensed one-dimensional (1-D) DCT and discrete sine transform (DST) with a regular preprocessing procedure. The recursive filters for condensed 1-D DCT/DST are then derived by using Chebyshev polynomials to compute M-D DCT/IDCT without data transposition. The proposed structures require fewer recursive loops than traditional 1-D recursive structures, which are realized in M passes and (M-1) data transposition by the so-called row-column approach. With advantages of fewer recursive loops and no transposition memory, the proposed structures attain more accurate results and less power consumption than traditional row-column structures. The proposed recursive M-D DCT/IDCT structures are suitable for very large-scale integration implementation due to regular and modular features.     

Biorthogonal and nonuniform lapped transforms for transform codingwith reduced blocking and ringing artifacts

New lapped transforms are introduced. The lapped biorthononal transform (LBT) and hierarchical lapped biorthogonal transform (HLBT) are appropriate for image coding, and the modulated HLBT biorthogonal transform (MMLBT) and nonuniform modulated lapped biorthogonal transform (NMLBT) are appropriate for audio coding. The HLBT has a significantly lower computational complexity than the lapped orthogonal transform (LOT), essentially no blocking artifacts, and fewer ringing artifacts than the commonly used discrete cosine transform (DCT). The LBT and HLBT have transform coding gains that are typically between 0.5 and 1.2 dB higher than that of the DCT. Image coding examples using JPEG and embedded zerotree coders demonstrate the better performance of the LET and HLBT. The NMLBT has fewer ringing artifacts and better reproduction of transient sounds than the MLT, as shown in audio coding examples. Fast algorithms for both the HLBT and the NMLBT are presented     

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     

Recompression of JPEG images by requantization

We report a novel heuristic for requantizing JPEG images. The resulting images are generally smaller and often have improved perceptual image quality over a "blind" requantization approach, that is, one that does not consider the properties of the quantization matrices. The heuristic is supported by a detailed mathematical treatment which incorporates the well-known Laplacian distribution of the AC discrete cosine transform (DCT) coefficients with an analysis of the error introduced by requantization. We note that the technique is applicable to any image compression method which employs discrete cosine transforms and quantization.