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。     

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。     

基于频谱偏移估计提高距离向分辨率处理算法的误差分析

基于频谱偏移估计算法是一种分布式小卫星合成孔径雷达(Distributed Small Satellite Synthetic Aperture Radar,简写为DSS-SAR)提高距离向分辨率的数据处理方法,它实现过程简洁、数据量小.从基于频谱偏移估计算法的实现过程知道,其性能主要受到频谱重叠和频谱偏移估计误差的影响,本文着重研究这两种误差因素对由该算法处理得到的合成图像质量的影响.分别推导了存在频谱重叠和频谱偏移估计误差时合成图像的数学表达式,分析了它们对合成图像质量的影响,提出了:1.频谱重叠主要引起合成图像中点目标旁瓣抬高;2.频谱偏移估计误差主要引起合成图像中点目标主瓣衰减和旁瓣抬高.利用点目标仿真验证了理论分析的正确性.最后根据误差分析结果,对基于频谱偏移估计算法的实现提出了改进的建议.     

任意方向匀速直线运动模糊的点扩展函数估计

在运动图像复原中,建立图像退化模型的关键是找到准确的点扩展函数(PSF)。提出了一种基于单幅图像的、改进的任意方向匀速直线运动模糊PSF的估计方法。利用基于图像频谱亮线灰度特征的方向鉴别方法鉴别模糊图像的模糊方向,利用微分自相关的方法对模糊图像的模糊尺寸进行计算,通过计算模糊图像沿二维直线运动方向不同距离的重叠度,来计算得到相应的PSF。通过开展仿真分析和成像实验,演示了PSF估计和图像复原过程。通过采用图像质量评价函数,将图像复原结果与现有算法进行对比,验证了所提出方法的有效性。     

基于频谱分布量化分析的星载人工目标快速检测方法

地物特征不单靠空域中像元灰度值的变化程度来表现,其频谱能够表征不同地物的特征,并可通过该频谱特征进行遥感图像的分析和目标的搜索、检测。提出一种通过频谱分析快速发现自然背景中人工目标及其所在区域的新方法,首先对图像的频谱分布特征进行了分析并提出了一种频谱分布量化的算法,定义频谱分布量化指数;根据计算出的区域频谱分布量化指数,借鉴视觉显著性的思想计算出各区域在整幅图像中的显著值,从而实现人工目标的检测。文中对该方法在海背景中舰船目标的检测和沙漠、戈壁中人工建筑的检测进行了实验,从结果可以看出新算法能够有效地实现自然背景潜在人工目标的快速搜索和发现,并确定出其所在区域,具有一定的灵活性,能够适应星上多变的检测场景。     

基于频谱偏移估计的分布式星载SAR提高距离向分辨率的数据处理方法

分布式星载SAR利用不同视角回波信号之间地面散射频谱不同的特性来提高SAR图像的距离向分辨率.其数据处理的关键就是如何将这些不同频段的信号相结合,得到具有更宽频谱的高分辨率图像.本文提出了一种基于频谱偏移估计的分布式星载SAR提高距离向SAR图像分辨率的数据处理方法.该方法的主要思想是在SAR复图像的基础上,通过精确的估计,得到SAR复图像间的距离向频谱偏移量,并根据该偏移量,在频域进行距离向频谱偏移补偿后将图像相加.建立了分布式星载SAR单视复图像的信号模型,推导了基于频谱偏移估计提高SAR图像距离向分辨率的原理公式,给出了基于频谱偏移估计提高距离向分辨率的具体数据处理步骤.最后采用仿真数据验证了理论推导的正确性和数据处理方法的有效性.     

红外焦平面阵列非均匀性自适应校正方法

分析基于场景的红外焦平面阵列非均匀性校正方法中的景物退化和鬼影现象,提出了一种基于边缘约束高斯滤波的红外焦平面阵列非均匀性自适应校正方法。该方法设计了一个边缘约束高斯滤波器来获取理想的估计图像,利用最陡下降法得到计算增益校正因子和偏移量校正因子的迭代公式,并通过迭代步长的自适应控制来增快算法的收敛速度。通过仿真实验和真实红外图像处理对比实验表明:相较于目前已有的方法,该方法在有效抑制景物退化和鬼影现象的同时,较好地去除原始红外图像的固定图案噪声,保留了图像细节信息,提高了图像质量。     

用于小波变换的图像信号二维频谱分析

本文在对理想和实际原始图像信号的二维频谱及其幅频特性进行数字分析的基础上，提出了对小波变换二维频谱分解的两种改进方案，从而可利用图像信号的频谱特性和人眼的视觉特性，进一步压缩码率，在保证图像质量的前提下，提高压缩性能。最后提出了设计菱形滤波器来获得原始图像信号二维菱形频谱的方案，该方案将在后继的论文中介绍。     

无线传感器网络中的轻量级协作频谱检测方法

探讨利用认知无线电技术为其寻求新的可用频谱资源,针对传感器网络资源受限的特点,提出了一种轻量级协作频谱检测方法.通过对采样信号进行量化,降低计算和通信开销,并从理论上分析了其检测性能.仿真结果表明,所提出的检测方法具有与非量化情况非常接近的检测性能,为在传感器网络中寻求可用频谱资源奠定了基础.     

基于Hough变换的散焦模糊图像复原方法

提出一种基于Hough变换的散焦模糊图像复原方法.首先分析了散焦模糊图像理论模型,并对其空域表现形式与频谱特性进行了分析.根据其特点,提出可利用Hough变换来对散焦模糊图像的模糊半径进行估计,进而确定对应的点扩散函数,结合维纳滤波复原图像.试验结果表明,该算法能较好地复原图像,有一定的抗噪声性能,并且具有计算量小、适合实时处理的优点.     

Novel approach based on deramping technique for squinted sliding spotlight SAR imaging

This paper investigates a novel approach based on the deramping technique for squinted sliding spotlight Synthetic Aperture Radar (SAR) imaging to resolve the azimuth spectrum aliasing problem. First of all, the properties of the azimuth spectrum and the squint angle impacts on the azimuth spectrum aliasing problem are analyzed. Based on the analysis result, an operation of filtering is added to the azimuth preprocessing step of traditional Two-Step Focusing Approach (TSPA) to resolve the azimuth folding problem and remove the influence of the squint angle on the azimuth spectrum aliasing problem. Then, a modified Range Migration Algorithm (RMA) is performed to obtain the precise focused image. Furthermore, the focused SAR image folding problem of traditional TSPA is illuminated in this paper. An azimuth post-processing step is proposed to unfold the aliased SAR image. Simulation experiment results prove that the proposed approach can solve the spectrum aliasing problem and process squinted sliding spotlight data efficiently.     

两阶段平移、旋转图像高精度配准算法

图像配准在图像处理中是十分重要的,通常是许多现代图像处理和计算机视觉任务一个关键的预处理步骤,许多算法和技术已经被提出用来解决配准问题.本文提出一种稳健的两阶段层次配准算法,在频域组合相位相关和谱对消技术对平移和旋转图像获得亚像素精度的配准.算法第一阶段首先利用一维FFT技术实现图像的旋转以确定旋转角度,并利用这个旋转角度将两幅图像之间的运动简化为平移运动,然后利用相位相关法确定整数像素平移参数.算法第二阶段运用谱对消技术确定亚像素平移参数.提出的算法甚至在图像因为下采样而包含混淆误差情况下仍然能够获得亚像素精度配准.     

Ordering for embedded coding of wavelet image data based on arbitrary scalar quantization schemes.

Many modern wavelet quantization schemes specify wavelet coefficient step sizes as continuous functions of an input step-size selection criterion; rate control is achieved by selecting an appropriate set of step sizes. In embedded wavelet coders, however, rate control is achieved simply by truncating the coded bit stream at the desired rate. The order in which wavelet data are coded implicitly controls quantization step sizes applied to create the reconstructed image. Since these step sizes are effectively discontinuous, piecewise-constant functions of rate, this paper examines the problem of designing a coding order for such a coder, guided by a quantization scheme where step sizes evolve continuously with rate. In particular, it formulates an optimization problem that minimizes the average relative difference between the piecewise-constant implicit step sizes associated with a layered coding strategy and the smooth step sizes given by a quantization scheme. The solution to this problem implies a coding order. Elegant, near-optimal solutions are presented to optimize step sizes over a variety of regions of rates, either continuous or discrete. This method can be used to create layers of coded data using any scalar quantization scheme combined with any wavelet bit-plane coder. It is illustrated using a variety of state-of-the-art coders and quantization schemes. In addition, the proposed method is verified with objective and subjective testing.     

Matlab仿真中变步长数据的FFT频谱分析

Matlab仿真输出的结果在很多情况下是变步长的时域信号,这时如果直接调用FFT函数对仿真结果进行频谱分析,结果往往是不准确的。本文针对这一情况,提出一种简单实用的方法:首先对变步长数据进行插值重构,变为等步长采样数据,再调用FFT进行频谱分析,则可以得到正确的结果。文中通过仿真实例验证了该方法的准确性。     

Optimal context quantization in lossless compression of image data sequences

In image compression context-based entropy coding is commonly used. A critical issue to the performance of context-based image coding is how to resolve the conflict of a desire for large templates to model high-order statistic dependency of the pixels and the problem of context dilution due to insufficient sample statistics of a given input image. We consider the problem of finding the optimal quantizer Q that quantizes the K-dimensional causal context Ct = (Xt-t1,Xt-t2,...,X t-tK) of a source symbol Xt into one of a set of conditioning states. The optimality of context quantization is defined to be the minimum static or minimum adaptive code length of given a data set. For a binary source alphabet an optimal context quantizer can be computed exactly by a fast dynamic programming algorithm. Faster approximation solutions are also proposed. In case of m-ary source alphabet a random variable can be decomposed into a sequence of binary decisions, each of which is coded using optimal context quantization designed for the corresponding binary random variable. This optimized coding scheme is applied to digital maps and alpha-plane sequences. The proposed optimal context quantization technique can also be used to establish a lower bound on the achievable code length, and hence is a useful tool to evaluate the performance of existing heuristic context quantizers.     

JPEG quantization step estimation with coefficient histogram and spectrum analyses

This paper proposes a new method for estimating quantization steps (QSs) from an image that has been previously JPEG-compressed and stored in a lossless format. In this method, DCT coefficients of each frequency band of JPEG-compressed image are aggregated in the QS and its multiples. The entire estimation process can be grouped into two categories: alternating and direct current bands. Considering that DCT coefficients under different QSs show different periodicity, QS estimation for each band is then further divided into three steps, which involve identifying whether the QS is one, two, or another value. For each step, the periodicity of DCT coefficients can be well exploited with the analyses of the DCT-coefficient histogram and its corresponding frequency magnitude spectrum. Experimental results demonstrate the efficacy of the proposed method and the superiority in QS estimation for previously JPEG-compressed images, especially in the case that the actual QSs are higher than two.     

皮肤图像的凹凸度和信息熵与年龄关系的研究

目的：常规手腕骨Tw3骨龄检测法不适用于骨骼停止发育的成年人的年龄检测,而人体皮肤在成年之后变化特征明显,通过求解皮肤特征参数与年龄关系,从而达到针对成年人年龄检测的目的。方法：采用医学图像处理技术,尤损检测并提取皮肤图像的量化参数凹凸度和信息熵,采用统计方法分析这些特征参数与年龄之间的关系。结果：成年人的年龄与皮肤图...     

基于量化的扩频水印技术

随着计算机和网络技术的飞速发展，数字图像、音频和视频产品越来越需要一种有效的版权保护方法，数字水印技术为上述问题提供了一个潜在的解决方案。提出了一种基子量化的扩频水印技术，算法将水印信号与序列作扩频调制，调制信号通过量化策略嵌入到块ＤＣＴ变换系数的低频分量中，在嵌入过程中考虑到了局部图像的复杂度，能够自适应地调整嵌入强度，提取水印信号无需使用原始图像。仿真实验表明水印是不可察觉的，经过 ＪＰＥＧ有损压缩、低通与中值滤波、剪切等图像处理操作后仍是稳健的。     

A multiscale error diffusion technique for digital multitoning

Multitoning is the representation of digital pictures using a given set of available color intensities, which are also known as tones or quantization levels. It can be viewed as the generalization of halftoning, where only two such quantization levels are available. Its main application is for printing and, similar to halftoning, can be applied to both colored and grayscale images. In this paper, we present a method to produce multitones based on the multiscale error diffusion technique. Key characteristics of this technique are: 1) the use of an image quadtree; 2) the quantization order of the pixels being determined through "maximum intensity guidance" on the image quadtree; and 3) noncausal error diffusion. Special care has been given to the problem of banding, which is one of the inherent limitations in error diffusion when applied to multitoning. Banding is evident in areas of the image with values close to one of the available quantization levels; our approach is to apply a preprocessing step to alleviate part of the problem. Our results are evaluated both in terms of visual appearance and using a set of standard metrics, with the latter demonstrating the blue-noise characteristics and very low anisotropy of the proposed method.