An efficient algorithm for optimizing DCT quantization

We describe the RD-OPT algorithm for DCT quantization optimization, which can be used as an efficient tool for near-optimal rate control in DCT-based compression techniques, such as JPEG and MPEG. RD-OPT measures DCT coefficient statistics for the given image data to construct rate/distortion-specific quantization tables with nearly optimal tradeoffs.     

并行处理JPEG算法的优化

本文结合指令级并行32位定点处理器的结构特点,对JPEG算法中DCT、量化及Huffman编码等步骤,提出一些适于并行处理算法和数据结构的优化方法,以有效发挥其高速并行的性能.模拟结果表明本文的方法显著提高了JPEG算法并行实现的效率,适于图像压缩的一些实时应用.     

基于上下文建模的分类排序小波图像编码算法

该文提出了基于上下文建模的分类排序小波图像编码算法。该方法使用与JPEG2000标准相同的上下文模型,以最小化相对熵为准则用动态规划获得优化的上下文分类。在重要性编码中结合优化的上下文分类进行排序编码。实验数据表明该算法的压缩能力优于JPEG2000,尤其适于低码率压缩。     

基于DCT域的菱形编码图像隐写改进算法

为提高嵌入秘密图像的信息量和嵌入后载体图像的质量,在行程编码、菱形编码和DCT域的基础上,提出了基于DCT域的菱形编码图像隐写改进算法.采用菱形编码有效地提高了嵌入率,对JPEG标准化量化表进行了改进,更有利于秘密信息的嵌入.对行程编码进行了改进,使秘密图像的压缩效率更大.经过与F5隐写算法对比实验表明,F5隐写算法只能嵌入一幅尺寸为64×64的灰度图像,而改进算法能够嵌入一幅尺寸为240×240的灰度图像,且PSNR＞ 30 dB,大大提高了加密信息的嵌入量,并保持了嵌入后载体图像的质量.     

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.     

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.     

JPEG-compliant perceptual coding for a grayscale image printingpipeline

We describe a procedure by which Joint Photographic Experts Group (JPEG) compression may be customized for gray-scale images that are to be compressed before they are scaled, halftoned, and printed. Our technique maintains 100% compatibility with the JPEG standard, and is applicable with all scaling and halftoning methods. The JPEG quantization table is designed using frequency-domain characteristics of the scaling and halftoning operations, as well as the frequency sensitivity of the human visual system. In addition, the Huffman tables are optimized for low-rate coding. Compression artifacts are significantly reduced because they are masked by the halftoning patterns, and pushed into frequency bands where the eye is less sensitive. We describe how the frequency-domain effects of scaling and halftoning may be measured, and how to account for those effects in an iterative design procedure for the JPEG quantization table. We also present experimental results suggesting that the customized JPEG encoder typically maintains "near visually lossless" image quality at rates below 0.5 b/pixel (with reference to the number of pixels in the original image) when it is used with bilinear interpolation and either error diffusion or ordered dithering. Based on these results, we believe that in terms of the achieved bit rate, the performance of our encoder is typically at least 20% better than that of a JPEG encoder using the suggested baseline tables.     

Joint thresholding and quantizer selection for transform imagecoding: entropy-constrained analysis and applications to baseline JPEG

Striving to maximize baseline (Joint Photographers Expert Group-JPEG) image quality without compromising compatibility of current JPEG decoders, we develop an image-adaptive JPEG encoding algorithm that jointly optimizes quantizer selection, coefficient "thresholding", and Huffman coding within a rate-distortion (R-D) framework. Practically speaking, our algorithm unifies two previous approaches to image-adaptive JPEG encoding: R-D optimized quantizer selection and R-D optimal thresholding. Conceptually speaking, our algorithm is a logical consequence of entropy-constrained vector quantization (ECVQ) design principles in the severely constrained instance of JPEG-compatible encoding. We explore both viewpoints: the practical, to concretely derive our algorithm, and the conceptual, to justify the claim that our algorithm approaches the best performance that a JPEG encoder can achieve. This performance includes significant objective peak signal-to-noise ratio (PSNR) improvement over previous work and at high rates gives results comparable to state-of-the-art image coders. For example, coding the Lena image at 1.0 b/pixel, our JPEG encoder achieves a PSNR performance of 39.6 dB that slightly exceeds the quoted PSNR results of Shapiro's wavelet-based zero-tree coder. Using a visually based distortion metric, we can achieve noticeable subjective improvement as well. Furthermore, our algorithm may be applied to other systems that use run-length encoding, including intraframe MPEG and subband or wavelet coding.     

一个优化小波块量化矩阵的算法

小波变换以其良好的空间－频率局部特性,在图像编码标准JPEG2000和MPEG4中占据了重要位置.本文选用正交小波基对图像做小波变换,然后重新组织小波系数成小波块,最后提出了一个构造小波块量化矩阵以产生最优比特分配的算法.本算法用一种新的方式统计小波系数分布,并结合人体视觉系统的特点,采用动态策略在很大的比特率范围内产生最优的小波块量化矩阵.     

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DCT变换的ROI嵌入式编码算法

JPEG是目前应用最广泛的静止图像压缩标准,将JPEG功能多样化具有重要意义。利用DCT变换比小波变换更加简单、快速的特点,结合SPIHT算法细化过程原理,实现了一种与JPEG标准兼容的ROI编码算法,既不增加编码时间,又可以实现ROI的渐进式增强传输,而且在图像重建质量稳定性和可控性方面要远远好于区域自适应量化编码,在较低码率下,仅增加少量码流就能够明显改善主观视觉感受。     

Rate distortion optimization for H.264 interframe coding: a general framework and algorithms.

Rate distortion (RD) optimization for H.264 interframe coding with complete baseline decoding compatibility is investigated on a frame basis. Using soft decision quantization (SDQ) rather than the standard hard decision quantization, we first establish a general framework in which motion estimation, quantization, and entropy coding (in H.264) for the current frame can be jointly designed to minimize a true RD cost given previously coded reference frames. We then propose three RD optimization algorithms--a graph-based algorithm for near optimal SDQ in H.264 baseline encoding given motion estimation and quantization step sizes, an algorithm for near optimal residual coding in H.264 baseline encoding given motion estimation, and an iterative overall algorithm to optimize H.264 baseline encoding for each individual frame given previously coded reference frames-with them embedded in the indicated order. The graph-based algorithm for near optimal SDQ is the core; given motion estimation and quantization step sizes, it is guaranteed to perform optimal SDQ if the weak adjacent block dependency utilized in the context adaptive variable length coding of H.264 is ignored for optimization. The proposed algorithms have been implemented based on the reference encoder JM82 of H.264 with complete compatibility to the baseline profile. Experiments show that for a set of typical video testing sequences, the graph-based algorithm for near optimal SDQ, the algorithm for near optimal residual coding, and the overall algorithm achieve on average, 6%, 8%, and 12%, respectively, rate reduction at the same PSNR (ranging from 30 to 38 dB) when compared with the RD optimization method implemented in the H.264 reference software.     

基于DCT和小波的图像和视频编码性能的比较研究

在比较编码性能时,许多人分析了图像和视频编码的离散余弦变换(DCT)和小波变换性能差别,普遍认为图像的小波编码在压缩比和编码质量方面优于传统的DCT变换编码.说明了研究图像和视频压缩算法应当从全面的系统观点来考虑,即把重点放在各要素之间的量化、熵编码和编码系统中的复杂的相互影响的研究上.     

On color transforms and bit allocation for optimal subband image compression

Although subband transform coding is a useful approach to image compression and communication, the performance of this method has not been analyzed so far for color images, especially when the selection of color components is considered. Obviously, the RGB components are not suitable for such a compression method due to their high inter-color correlation. On the other hand, the common selection of YUV or YIQ is rather arbitrary and in most cases not optimal. In this work we introduce a rate–distortion model for color image compression and employ it to find the optimal color components and optimal bit allocation (optimal rates) for the compression. We show that the DCT (discrete cosine transform) can be used to transform the RGB components into an efficient set of color components suitable for subband coding. The optimal rates can be also used to design adaptive quantization tables in the coding stage with results superior to fixed quantization tables. Based on the presented results, our conclusion is that the new approach can improve presently available methods for color image compression and communication.     

一种新的静止图象压缩编码算法

本文提出了一种新的静止图象压缩编码算法,即VQ+DPCM+DCT算法,并与JPEG标准的基本系统进行了比较。实验结果表明,新算法的压缩比有较大提高。     

一种结合人眼对比度感知特性的彩色图像压缩算法

为了使图像压缩后的效果更加符合人眼感知特性,提出了一种结合人眼对比度敏感视觉特性的图像压缩算法。算法首先结合视觉特性和图像变换域频谱系数特征,提出一种图像的角频率的计算方法,并依据计算的角频率提出一种人眼觉察图像最小误差阈值的计算方法;然后以此阈值作为量化步长,提出一种图像变换域频谱系数的量化方法;最后采用霍夫曼编码算法进行编解码,实现图像的压缩。并对三幅彩色图像进行了仿真实验,结果表明:与JPEG技术相比,三幅彩色图和各分量图的平均压缩比、PSNR和SSIM依次提高了10.4807%、6.9879%和2.6494%。表明提出的结合人眼视觉特性的图像压缩算法是一种较好的、有实用价值的压缩算法。     

图像压缩编码中Walsh变换与DCT变换及其比较

图像变换是图像处理的基础,是图像压缩的第一步。在图像压缩中,DCT变换因其变换效果好而被广泛采用,成为目前最常用的图像压缩变换方法,而Walsh变换还未被广泛采用。通过对这两种变换的算法分析以及Matlab仿真实验和峰值信噪比的对比,结果表明,walsh变换在算法上比DCT简单,实现较为容易,其变换性能并不亚于DCT变换,在某些量化级上甚至还优于DCT变换,Walsh变换有着广泛的应用前景。     

基于DCT变换的内嵌静止图像压缩算法

提出了一种有效的基于离散余弦变换(DCT)的内嵌子带图像编码算法.Xiong等人提出的EZDCT算法采用零树结构实现了一种内嵌DCT编码器,且其性能优于JPEG.本文指出DCT的零树结构在内嵌DCT算法中并非很有效,同时提出了一种不依赖零树结构的简便、高效的内嵌DCT子带编码算法.实验结果表明本文算的压缩性能(PSNR)比EZDCT高约0.5~1.5dB,且接近当前最通用的内嵌小波SPIHT算法,在对某些图像压缩时还优于SPIHT算法.     

多光谱图像的信息分析及数据压缩

首先利用条件熵对成像光谱仪多光谱图像在空间维和光谱维方向的信息冗余度进行了分析，结果表明成像光谱图像在空间维具有很强的相关性，而在光谱维方向，图像信息不平稳，相关性略小。然后对标准的基于JPEG量化表进行改进，提出了一种既能有效保真图像边缘信息，又能提高压缩倍数的改进JPEG压缩算法-I-JPEG。随后又提出了I-JPEG／DPCM压缩算法。这种方法在I-JPEG基础上，利用局部化特性较好的无损DPCM方法去除图像在光谱维的相关性，使压缩性能得到进一步提高。