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。     

基于人眼对比度敏感视觉特性的彩色图像压缩技术

结合人眼对比度敏感视觉特性的测量过程和图像离散余弦变换特征,提出了一种基于人眼感知特性的彩色图像压缩技术方案。方案首先将彩色图像转换到CLELAB颜色空间描述,并分别对3个分量进行离散余弦变换处理,再结合人眼对比度敏感函数模型和DCT变换域系数特征对变换域系数进行量化处理,并采用Huffman算法进行编码压缩,最后采用逆过程进行解压并匹配出解压后的彩色图像。通过仿真实验,结果表明:在压缩比为98.355 5∶1时,PSNR能达到37dB以上,人眼无法分辨出解压缩图像与源图像之间的差异;且编码效率能达到0.74以上,冗余度在0.26以下。表明提出的彩色图像的压缩技术方案在保证编码质量和图像质量的前提下能够实现较高的压缩比,是一种可行的、有效的彩色图像压缩技术方案。     

遥感图像自适应分层量化的快速DCT压缩法

依据遥感图像的频谱特性,提出一种自适应分层量化的快速DCT图像压缩算法,在对原始图像快速DCT之后,根据图像频谱特性自适应修正JPEG量化表,再用新量化表分层量化DCT系数。真实遥感图像压缩实验表明,在同等压缩比下,提出的方法比标准JPEG方法速度快,且峰值信噪比增加1～2dB,并能实现嵌入式码流图像压缩。     

离散彩色图像可视模型与快速聚类技术研究

本文研究了离散彩色图像视觉特征模型,提出了图像可视信息熵、可视质量SNR(VPSNR)、步进聚类等概念;并在该模型基础上,针对离散彩色图像的高效压缩,提出了一种快速聚类算法。算法根据图像HSV空间的特性和空域分布特性进行聚类和量化。在保证图像主观视觉质量不变的情况下,使图像的信息数据充分接近可视信息熵.将离散彩色图像视觉特征模型和聚类技术应用于离散彩色图像的压缩,实验表明系统压缩率可达60～300,与JPEG相比有明显的提高,提得平均压缩率约为JPEG的6倍。     

JPEG2000小波域隐写算法

针对JPEG2000基本压缩编码系统,提出一种基于冗余估算的小波域隐写算法(RE-WDS)。利用JPEG2000标准扩展部分中规定的对量化前小波系数的非线性处理方法,以及人眼的亮度敏感性特点,对每个小波系数的量化冗余进行估算,做到隐写算法与人眼掩蔽特性紧密结合。通过自适应地选择嵌入点并对嵌入强度进行调整,来提高压缩图像的信息隐藏容量,仿真实验证明了算法的可行性和有效性。     

基于分块量化的小波域数字水印嵌入算法

提出了一种基于分块量化的小波域数字水印嵌入算法，该算法具有如下特点：（1）以图像局部相关特性为基础，采纳了分块量化策略；（2）以人眼视觉感知特性为基础，构造了量化步长的自适应选取方案；（3）结合误检概率分析。给出了检测阚值T的一般性选取方法。仿真实验表明，该算法不仅具有较好的透明性，而且对诸如叠加噪声、JPEG压缩、平滑滤波、几何剪切、图像增强等攻击均具有较好的鲁棒性。     

基于自适应频带选择的数字水印技术

如何选择水印的隐藏区域是水印算法中的关键问题。该文提出了一种自适应DCT域水印算法,利用了人眼视觉系统(HVS)和图像局部特性自适应地选择水印隐藏区域,有效地实现了水印的稳定性和不可见性的折衷。与其它水印算法比较,该文提出的自适应算法适合于具有不同总体特性和局部特性的图像。实验结果表明该算法具有很好的感知质量,水印稳健性好,可以抵制各种图像处理操作诸如加性白噪声(AWGN),JPEG压缩以及裁剪,中值滤波,缩放等。     

基于JPEG双量化特性的彩色伪造图像盲检测

现有的盲检测方法主要针对灰度图像和未压缩图像,很多算法都不能有效地检测彩色压缩伪造图像。本文提出了一种利用JPEG双量化失真特性实现彩色压缩伪造图像盲检测的方法。通过分析伪造图像的制作过程,可知由多幅JPEG图像拼接成的高质量彩色伪造图像中篡改区域和背景区域经历的双量化过程不同。根据这一特性,本文首先使用背景区域的初始量化表估计值对待检测图像进行再压缩处理,定义再压缩后图像各颜色分量的失真函数;然后根据各失真函数在图像不同区域的取值,由各颜色分量分别确定篡改区域;最后综合彩色图像各颜色分量的检测结果,最终识别出彩色图像篡改区域的位置和大小。仿真结果表明该方法不但可以有效地识别彩色伪造图像的篡改区域,而且比基于单一颜色分量的检测方法更加准确。      

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。     

基于小波零树的图像感知熵编码研究

本文以小波作为编码框架,通过对人工合成图像的主观实验,得出小波变换域中各不同频带的视觉误差阈值函数,进而提出了一个新的量化编码方案。该方案基于小波域非均匀零树结构量化和高频低能系数的视觉非均匀量化。对实际图像的感知熵和几乎透明的情形作了研究,与JPEG标准也作了比较。实验表明该方案较充分、自适应地考虑人眼视觉冗余,具有稳健、实际可行的特点。对自然图像,在十倍压缩比左右可有视觉无失真质量。     

A Novel Scheme for Compression of Cash Images

In the field of economy, there are more and more electronic scanning cash images, which need to be compressed in a higher compression ratio. This paper proposes a specific compression algorithm for cash images. First, according to cash image characteristics and standard JPEG (joint photographic experts group) compression, image re-ordering techniques are analyzed, and the method of modifying some blocks into single color blocks is adopted. Then, a suitable quantization table for cash images is obtained. Experimental results show that the method is effective.     

采用超分辨率重建提升压缩图像质量的方法

针对JPEG的中低码率压缩图像即高压缩率图像存在较严重的块效应以及量化噪声,提出了一种对JPEG标准压缩图像进行优化的重建-采样方法.该方法对JPEG压缩图像采用三维块匹配算法(BM3D)进行去噪,去除图像中存在的块效应和量化噪声,进而提高超分辨率重建的映射准确性,再使用外部库对去噪后图像进行基于稀疏表示的超分辨率重建,补充一定的高频信息,最后对重建后的高分辨率图进行双三次下采样,得到与原始图像大小一致的图像作为最终优化图像.实验结果表明,该方法在中低码率情况下能够有效地提高JPEG压缩图像的质量,对高码率压缩图像也有一定效果.     

Identification of bitmap compression history: JPEG detection and quantizer estimation

Sometimes image processing units inherit images in raster bitmap format only, so that processing is to be carried without knowledge of past operations that may compromise image quality (e.g., compression). To carry further processing, it is useful to not only know whether the image has been previously JPEG compressed, but to learn what quantization table was used. This is the case, for example, if one wants to remove JPEG artifacts or for JPEG re-compression. In this paper, a fast and efficient method is provided to determine whether an image has been previously JPEG compressed. After detecting a compression signature, we estimate compression parameters. Specifically, we developed a method for the maximum likelihood estimation of JPEG quantization steps. The quantizer estimation method is very robust so that only sporadically an estimated quantizer step size is off, and when so, it is by one value.     

自适应抖动调制图像水印算法

量化步长是影响量化水印算法性能的最关键因素之一。该文根据JPEG量化表自适应地选择抖动调制中的量化步长,提出了一种新的自适应量化水印算法;并将JPEG量化表和Watson感知模型相结合提出了另一种新的自适应量化水印算法。实验结果表明该文提出的两种算法对噪声干扰和常见的图像处理具有较好的鲁棒性。此外,研究还表明JPEG量化表和Watson模型均可以用于缓解量化水印算法对噪声的敏感程度,而结合了两者的水印算法可以获得最佳性能。     

Improving JPEG performance in conjunction with cloud editing forremote sensing applications

The authors propose an improved version of JPEG coding for compressing remote sensing images obtained by optical sensors onboard microsatellites. The approach involves expanding cloud features to include their cloud-land transitions, thereby simplifying their coding and subsequent compression. The system is fully automatic and appropriate for onboard implementation. Its improvement in coding stems from the realization that a large number of bits are used for coding the blocks that contain the transition regions between bright clouds, if present in the image, and the dark background. A fully automatic cloud-segmentation algorithm is therefore used to identify the external boundaries of the clouds, then smooth the corresponding blocks prior to coding. Further gains are also achieved by modifying the quantization table used for coding the coefficients of the discrete cosine transform. Compared to standard JPEG, at the same level of reconstruction quality, the new method can achieve compression ratio improvement by 13-161%, depending upon the context and the amount of cloud present in the specific image. The results are demonstrated with the help of several real images obtained by the University of Surrey, U.K., satellites     

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。     

Dictionary based surveillance image compression

Common image compression techniques suitable for general purpose may be less effective for such specific applications as video surveillance. Since a stationed surveillance camera always targets at a fixed scene, its captured images exhibit high consistency in content or structure. In this paper, we propose a surveillance image compression technique via dictionary learning to fully exploit the constant characteristics of a target scene. This method transforms images over sparsely tailored over-complete dictionaries learned directly from image samples rather than a fixed one, and thus can approximate an image with fewer coefficients. A set of dictionaries trained off-line is applied for sparse representation. An adaptive image blocking method is developed so that the encoder can represent an image in a texture-aware way. Experimental results show that the proposed algorithm significantly outperforms JPEG and JPEG 2000 in terms of both quality of reconstructed images and compression ratio as well.     

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.