基于颜色色差的彩色图像压缩技术研究

根据图像DCT变换域系数特征和结合人眼辨别颜色色差的阈值,提出了一种基于颜色色差的彩色图像压缩技术方案。方案首先将彩色图像转化到与设备无关的CIELAB颜色空间,并进行DCT变换和色差计算;再通过人眼辨别颜色色差的阈值进行有选择的量化,并通过Huffman算法进行编码、压缩;最后利用其逆过程进行解压。通过仿真实验,结果表明,重建的彩色解压缩图像与源图像几乎一样,各分量亮度图的解压缩图像的PSNR均超过30dB,人眼几乎不能分辨其差异;衡量编码质量优劣的5个参数值均达到较好效果,且在保证解压缩图像质量的情况下,彩色图像的压缩比能够达到107.167 8,完全可以满足彩色图像压缩的需求。结果表明,提出的基于颜色色差的图像压缩技术方案是一种可行的、较好的彩色图像压缩技术。     

A practical adaptive image compression technique using visualcriteria for still-picture transmission with electronic mail

An efficient image compression/decompression technique for complex scenes is presented. An image is first decorrelated by a full two-dimensional DCT (discrete cosine transform). The resulting coefficient map is weighted using properties of the human visual system and finally encoded with a novel multiresolution encoder. The result is converted into printable ASCII for transmission by electronic mail     

Image/video spatial scalability in compressed domain

Image/video compression is widely used in various applications with the advent of the Joint Photographic Expert Group (JPEG), Motion Picture Expert Group (MPEG), and H.261 standards. Hence, most visual data are stored in the compressed format. Spatial scalable encoding of visual data has several applications, including browsing visual databases, querying multimedia databases, interactive multimedia communications, etc. We propose two novel techniques, namely, format compatible (FC) discrete cosine transform (DCT) and format modified (FM) DCT to implement image/video spatial scalability directly in the DCT compressed domain. The FC-DCT technique can be used to manipulate the standard bit streams, such as JPEG, MPEG, etc., while the FM-DCT technique can be employed in a variety of applications which require fast processing. In contrast to the traditional spatial-domain techniques, the compressed-domain techniques remove the unnecessary decompression and recompression procedures, thus, they have the advantages of reduced computational complexity and storage requirements. Simulation results demonstrate that the proposed DCT-domain techniques can achieve a comparable performance at a much lower computational complexity compared to the spatial-domain techniques     

宽带回波信号的非线性幅相压缩性能分析

为了在雷达回波数据压缩中较好地保留目标的相位信息,研究了基于非线性离散余弦变换(DCT)和自适应小波贪婪(AWG)算法的幅相压缩性能。运用上述2种算法对宽带回波信号分别进行了正交I/Q压缩和幅相压缩实验。通过性能指标CSNR(压缩信噪比)和CPSD(压缩相位标准差),比较了I/Q压缩和幅相压缩的压缩性能。结果表明,同传统的I/Q压缩相比,幅相压缩能很好地保留目标的幅相信息;上述2种幅相压缩方法在不同信噪比情况下各有优势,非线性DCT幅相压缩适宜于压缩低信噪比宽带回波信号,基于AWG算法的幅相压缩则适宜于压缩高信噪比回波信号。     

A video-rate JPEG chip set

A two-chip set has been designed, fabricated and is fully functional which performs the baseline JPEG image compression and decompression algorithm. The major functions of the devices include: DCT and IDCT, forward and inverse quantization, Huffman coding and decoding. The devices operate with pixel rates beyond 30 MHz at 70 degrees C and 4.75 V. Each die is less than 10 mm on a side and was implemented in a 1.0 µ CMOS cell-based technology to achieve a 9 man-month design time.     

A video-rate JPEG chip set

A two-chip set has been designed, fabricated and is fully functional which performs the baseline JPEG image compression and decompression algorithm. The major functions of the devices include: DCT and IDCT, forward and inverse quantization, Huffman coding and decoding. The devices operate with pixel rates beyond 30 MHz at 70 degrees C and 4.75 V. Each die is less than 10 mm on a side and was implemented in a 1.0 µ CMOS cell-based technology to achieve a 9 man-month design time.     

Manipulation and compositing of MC-DCT compressed video

Many advanced video applications require manipulations of compressed video signals. Popular video manipulation functions include overlap (opaque or semitransparent), translation, scaling, linear filtering, rotation, and pixel multiplication. We propose algorithms to manipulate compressed video in the compressed domain. Specifically, we focus on compression algorithms using the discrete cosine transform (DCT) with or without motion compensation (MC). Such compression systems include JPEG, motion JPEG, MPEG, and H.261. We derive a complete set of algorithms for all aforementioned manipulation functions in the transform domain, in which video signals are represented by quantized transform coefficients. Due to a much lower data rate and the elimination of decompression/compression conversion, the transform-domain approach has great potential in reducing the computational complexity. The actual computational speedup depends on the specific manipulation functions and the compression characteristics of the input video, such as the compression rate and the nonzero motion vector percentage. The proposed techniques can be applied to general orthogonal transforms, such as the discrete trigonometric transform. For compression systems incorporating MC (such as MPEG), we propose a new decoding algorithm to reconstruct the video in the transform domain and then perform the desired manipulations in the transform domain. The same technique can be applied to efficient video transcoding (e.g., from MPEG to JPEG) with minimal decoding     

A 0.9-V, 150-MHz, 10-mW, 4 mm2, 2-D discrete cosinetransform core processor with variable threshold-voltage (VT)scheme

A 4 mm², two-dimensional (2-D) 8×8 discrete cosine transform (DCT) core processor for HDTV-resolution video compression/decompression in a 0.3-μm CMOS triple-well, double-metal technology operates at 150 MHz from a 0.9-V power supply and consumes 10 mW, only 2% power dissipation of a previous 3.3-V design. Circuit techniques for dynamically varying threshold voltage (VT scheme) are introduced to reduce active power dissipation with negligible overhead in speed, standby power dissipation, and chip area. A way to explore V _DD-V_th design space is also studied     

A CMOS image sensor with analog two-dimensional DCT-basedcompression circuits for one-chip cameras

This paper presents a CMOS image sensor with on-chip compression using an analog two-dimensional discrete cosine transform (2-D DCT) processor and a variable quantization level analog-to-digital converter (ADC). The analog 2-D DCT processor is essentially suitable for the on-sensor image compression, since the analog image sensor signal can be directly processed. The small and low-power nature of the analog design allows us to achieve low-power, low-cost, one-chip digital video cameras. The 8×8-point analog 2-D DCT processor is designed with fully differential switched-capacitor circuits to obtain sufficient precision for video compression purposes. An imager array has a dedicated eight-channel parallel readout scheme for direct encoding with the analog 2-D DCT processor. The variable level quantization after the 2-D DCT can be performed by the ADC at the same time. A prototype CMOS image sensor integrating these core circuits for compression is implemented based on triple-metal double-polysilicon 0.35-μm CMOS technology. Image encoding using the implemented analog 2-D DCT processor to the image captured by the sensor is successfully performed. The maximum peak signal-to-noise ratio (PSNR) is 36.7 dB     

基于DCT的图像运动补偿预测算法及其优化

数据压缩已成为当前多媒体技术发展的一个瓶颈问题，而对于影视图像压缩算法的研究，更是多媒体发展的重中之重。将要介绍的就是一种基于DCT的运动补偿算法及其相应的优化。其中也包括对一些重要概念，如ICT，DCT等的介绍。     

Image representation using block compressive sensing for compression applications

The emerging compressive sensing (CS) theory has pointed us a promising way of developing novel efficient data compression techniques, although it is proposed with original intention to achieve dimension-reduced sampling for saving data sampling cost. However, the non-adaptive projection representation for the natural images by conventional CS (CCS) framework may lead to an inefficient compression performance when comparing to the classical image compression standards such as JPEG and JPEG 2000. In this paper, two simple methods are investigated for the block CS (BCS) with discrete cosine transform (DCT) based image representation for compression applications. One is called coefficient random permutation (CRP), and the other is termed adaptive sampling (AS). The CRP method can be effective in balancing the sparsity of sampled vectors in DCT domain of image, and then in improving the CS sampling efficiency. The AS is achieved by designing an adaptive measurement matrix used in CS based on the energy distribution characteristics of image in DCT domain, which has a good effect in enhancing the CS performance. Experimental results demonstrate that our proposed methods are efficacious in reducing the dimension of the BCS-based image representation and/or improving the recovered image quality. The proposed BCS based image representation scheme could be an efficient alternative for applications of encrypted image compression and/or robust image compression.     

Study on the distribution of DCT residues and its application to R-D analysis of video coding

Quantization errors in discrete-cosine-transform (DCT) video compression are known as DCT residues. Knowledge on their distribution is essential in understanding rate-distortion (R-D) behaviors of generic video coding. Traditional R-D analysis adopted a simplified distortion model. Those distortion models took only quantization parameter into account. They lack adaptability to variation of video sources, as the distribution of coding errors also depends on the statistics of video source. Another common approach models the distribution of DCT residues by fitting experimental data from coded pictures to conjectured statistical distributions, but it did not provide insights into what gives rise to the distribution of DCT residues. This paper intends to quantify the distribution of DCT residues with respect to video source and with respect to the quantization strategy by understanding the quantization of DCT frequency components. Moreover, it is applied to derive an R-D model to show the advantage of the proposed distribution model.     

Lossy-to-lossless image compression based on multiplier-less reversible integer time domain lapped transform

In this paper, a reversible integer to integer time domain lapped transform (RTDLT) is introduced. TDLT can be taken as a combination of time domain pre- and post-filter modules with discrete cosine transform (DCT). Different from TDLT, the filters and DCT in our proposed RTDLT are realized from integer to integer by multi-lifting implementations after factorizing the filtering and transforming matrixes into triangular elementary reversible matrices (TERMs). Lifting implementations are realized by only shift and addition without any floating-point multiplier to reduce complexity. The proposed method can realize progressive lossy-to-lossless image compression with a single bit-stream. Simulation results show that RTDLT-based compression system obtains comparable or even higher compression-ratio in lossless compression than that of JPEG2000 and JPEG-LS, as well as gratifying rate distortion performance in lossy compression. Besides, RTDLT keeps low-complexity in hardware realization because it can be parallel implemented on the block level.     

一种用于实时视频处理的高速二维DCT的电路设计和实现

绝大多数的国际图像和视频压缩标准都采用DCT(离散余弦变换)进行传输编码。本文介绍了一种基于矩阵分解算法的高速实时二维DCT处理器。为了满足视频处理的实时性，整个电路设计中广泛采用了流水线技术，文中详细介绍了二维DCT处理器的电路结构，最后给出了它的FPGA实现。     

Image extraction in DCT domain

More and more digital images are being stored in compressed formats, among which the format using discrete cosine transform (DCT) coefficients is widely adopted (JPEG, MPEG, H.263 etc). To exploit those successful image processing techniques developed in the pixel domain, the authors propose a fast image extraction algorithm to allow images to be extracted directly from compressed DCT coefficients without full decompression. In the proposed technique the extracted images retain quality comparable with that of fully decoded images. However, the computing cost and the storage expense incurred by the proposed algorithm are very much lower than the costs of full decompression. The experiments also demonstrate that the proposed algorithm has tremendous potential in that all existing image processing techniques developed in the pixel domain can be directly applied to compressed images, without involving full decompression.     

The discrete modal transform and its application to lossy image compression

This paper introduces the discrete modal transform (DMT), a 1D and 2D discrete, non-separable transform for signal processing, which, in the mathematical sense, is a generalization of the well-known discrete cosine transform (DCT). A 3D deformable surface model is used to represent the image intensity and the introduced discrete transform is a by-product of the explicit surface deformation governing equations. The properties of the proposed transform are similar to those of the DCT. To illustrate these properties, the proposed transform is applied to lossy image compression and the obtained results are compared to those of a DCT-based compression scheme. Experimental results show that DMT, which includes an embedded compression ratio selection mechanism, has excellent energy compaction properties and achieves comparable compression results to DCT at low compression ratios, while being in general better than DCT at high compression ratios.     

ECG data compression using cut and align beats approach and 2-D transforms

A new electrocardiogram (ECG) data compression method is presented which employs a two dimensional (2-D) transform. This 2-D transform method utilizes the fact that ECG signals generally show two types of redundancies--between adjacent heartbeats and between adjacent samples. A heartbeat data sequence is cut and beat-aligned to form a 2-D data array. Any 2-D compression method can then be applied. Transform coding using the 2-D discrete cosine transform (DCT) [2-D DCT] is employed here as an example. Using selections from the MIT-BIH arrhythmia and Medtronic databases, results are presented that illustrate substantial improvement in compression ratio over one-dimensional methods for comparable percent root-mean-square difference (PRD).     

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.     

A low-power DCT core using adaptive bitwidth and arithmeticactivity exploiting signal correlations and quantization

This work describes the implementation of a discrete cosine transform (DCT) core compression system targetted to low-power video (MPEG2 MP@ML) and still-image (JPEG) applications. It exhibits two innovative techniques for arithmetic operation reduction in the DCT computation context along with standard voltage scaling techniques such as pipelining and parallelism. The first method dynamically minimizes the bitwidth of arithmetic operations in the presence of data spatial correlation. The second method trades off power dissipation and image compression quality (arithmetic precision). The chip dissipates 4.38 mW at 14 MHz and 1.56 V     

Motion analysis in 3D DCT domain and its application to video coding

Global, constant-velocity, translational motion in an image sequence induces a characteristic energy footprint in the Fourier-transform (FT) domain; spectrum is limited to a plane with orientation defined by the direction of motion. By detecting these spectral occupancy planes, methods have been proposed to estimate such global motion. Since the discrete cosine transform (DCT) is a ubiquitous tool of all video compression standards to date, we investigate in this paper properties of motion in the DCT domain. We show that global, constant-velocity, translational motion in an image sequence induces in the DCT domain spectral occupancy planes, similarly to the FT domain. Unlike in the FT case, however, these planes are subject to spectral folding. Based on this analysis, we propose a motion estimation method in the DCT domain, and we show that results comparable to standard block matching can be obtained. Moreover, by realizing that significant energy in the DCT domain concentrates around a folded plane, we propose a new approach to video compression. The approach is based on 3D DCT applied to a group of frames, followed by motion-adaptive scanning of DCT coefficients (akin to “zig-zag” scanning in MPEG coders), their adaptive quantization, and final entropy coding. We discuss the design of the complete 3D DCT coder and we carry out a performance comparison of the new coder with ubiquitous hybrid coders.