基于区域分割的分形图像压缩编码方法

在基于块分割的分形图像压缩编码研究基础上，提出了一种基于区域分割和十字搜索模型的分形图像压缩编码新方法，实验结果表明，该方法与基于块分割的分形图像压缩编码方法相比，在保持恢复图像质量的前提下，压缩比和编码速度都有了显著的提高，是一种有效的分形图像压缩编码方法。     

分形图像编码的原理及其发展趋势

介绍了分形图像编码的原理及分形图像压缩的编码方法，提出了分形图像压缩编码的改进方法及其发展趋势。     

基因表达式编程在分形图像压缩编码中的应用

针对目前存在图像压缩率不高、全局搜索或遗传算法寻找最优分形图像压缩编码速度慢的不足,将基因表达式编程应用于分形图像压缩编码,提高求解分形图像压缩编码速度和压缩比.首先从理论上对二值图像压缩编码的求解过程和基因表达式编程在压缩编码中的作用机理进行分析;然后,研究分形图像压缩编码的基因和染色体的表示方法,适应度函数设计以及选择、变异、插串、基因变换、基因重组等基因遗传进化操作过程.提出基因表达式编程的分形图像压缩算法,求解分形图像压缩编码的最优解.实验结果表明,基因表达式编程应用于分形图像压缩编码,具有较强的全局寻优能力,搜索最优解的速度比遗传算法快约2倍,图像压缩率高.     

分形图像压缩

欧氏几何学不能处理自然界中非常复杂的形状，这只能借助于分形几何学，分形图像压缩就是利用分形几何学的有关原理进行编码，达到图像压缩之目的。     

基于深度学习的分形图像压缩编码模型设计

针对传统编码模型存在的图像分割处理效果不佳、分割精度不高、耗时较长以及编码质量较差的问题，提出基于深度学习的分形图像压缩编码模型。建立图像分割约束条件，对图像进行分割处理，以处理后的图像作为深度学习中ResNet网络模型的输入，提取原始分形图像的特征并将图像块分类；建立特征图像块匹配规则，排序图像块，记录分形码，将分形码作为图像在度量空间内的表现形式，通过度量空间的压缩变换实现分形图像压缩编码。实验结果表明：所提模型的图像压缩编码质量较高，具有一定的应用价值。     

小波分形混合图像压缩编码进展

介绍了分形、小波图像压缩编码进展情况，简要讨论了小波分形混合图像压缩的一般方法，并对国内外小波分形图像压缩的现状进行了详细的说明，探讨了静止图像压缩编码的发展方向。     

基于平方加权质心特征的快速分形图像压缩编码

分形图像压缩利用自身图像具有的相似性,结合压缩仿射变换减少图像数据的冗余来实现图像数据的压缩,具有压缩比高、恢复简单的特点。然而,分形图像压缩编码也具有编码时间长、计算复杂的缺点。为了解决上述的缺点,提出了基于平方加权质心特征的快速分形图像压缩编码算法,利用平方加权质心特征可以将基本分形图像压缩编码过程中的全局搜索转化为局部搜索,限定搜索范围,减少码本数量,在巨大图像信息量传输和存储过程中,在一定程度上缩短了编码时间。将平方加权质心特征快速分形图像压缩编码算法和双交叉和算法、改进叉迹算法、规范五点和算法进行比较,仿真结果表明,所提算法在恢复质量可接受情况下,编码时间具有巨大优势。     

图像压缩编码方法分析

介绍图像压缩编码技术发展过程,对图像压缩编码,特别是自适应预测编码、模型法编码、分形编码、小波变换压缩编码、神经网络压缩编码原理和特点进行分析,并阐述图像压缩编码的作用.     

一种改进的分形图像压缩算法

为了提高分形图像压缩编码的速度,针对在基本分形图像压缩算法中值域块编码匹配搜索时需要对变换后的定义域块一一对应,导致编码时间较长的缺点,提出了一种基于菱形搜索算法的分形图像压缩编码新算法.菱形搜索算法是一种运动估计的快速搜索算法,主要过程是在所有的候选块中搜索当前块的最优匹配块.通过运用菱形搜索算法中的大小菱形模板进行匹配搜索,实验证明文中算法在提高编码速度和降低编码复杂度是有效的.     

基于混合编码的分形图像压缩方法研究

提出了一种基于混合编码的分形图像压缩方案,改进了分形编码与SP IHT算法,对提升小波变换后的最低频部分采用改进的分形编码,其他部分采用改进的SP IHT算法。试验结果表明,该方法在缩短了图像压缩时间的同时,明显减少了分形压缩恢复图像的方块效应。     

基于亚取样分形插值预测的混合图像编码方法

提出了一种基于亚取样分形插值预测的混合图像编码方法。将原始图像在水平方向和垂直方向皆作１／２抽取得到一幅“亚抽图像”，对亚抽图像进行分形编码得到亚抽图像的分形码，采用分形插值方法由亚抽图像的分形码解码得到原始图像的分形预测图像，然后对预测误差图像进行基于ＤＣＴ的自适应补偿编码。实验表明，这种方法的编码速度有了很大提高，而且恢复图像的质量具有较高的保真度。     

分形插值和分形图象压缩编码相结合进行图象数据压缩

本文首先研究了分形图象压缩编码和分形插值图象压缩方法。这两种方法在压缩比很高时图象效果均不是很理想,为此我们提出了综合利用分形插值和分形图象编码方法进行图象数据高效压缩的思想。实验结果验证了这种思想的正确性和可行性。新的方法在恢复图象信噪比为28.5dB时,压缩倍数可高达76倍,速度也大大提高。     

Content-based image retrieval using block-constrained fractalcoding and nona-tree decomposition

Fractal coding has been proved useful for image compression. In fractal coding, an image is represented by a number of self-transformations (fractal code) by which an approximation of the original image can be reconstructed. The authors present a block-constrained fractal coding scheme and a nona-tree decomposition based matching strategy for content-based image retrieval. In the coding scheme, an image is partitioned into non-overlapped blocks with a size close to that of a query iconic image. The fractal code is generated for each block independently. In the similarity measure of the fractal code, an improved nona-tree decomposition scheme is adopted to avoid matching the fractal code globally in order to reduce computational complexity. The experimental results show that the authors' coding scheme and matching strategy are useful for image retrieval, and compare favourably with two other methods tested in terms of storage usage and computing time     

Iteration-free fractal image coding based on efficient domain pooldesign

The domain pool design is one of the dominant issues which affect the coding performance of fractal image compression. In this paper, we employ the LBG algorithm and propose a block averaging method to design the efficient domain pools based on a proposed iteration-free fractal image codec. The redundancies between the generated domain blocks are reduced by the proposed methods. Therefore, we can obtain the domain pools that are more efficient than those in the conventional fractal coding schemes and thus the coding performance is improved. On the other hand, the iteration process in the conventional fractal coding scheme not only requires a large size of memory and a high computation complexity but also prolongs the decoding process. The proposed iteration-free fractal codec can overcome the problems above. In computer simulation, both the LBG-based and block-averaging methods for the domain pool design in the proposed iteration free scheme achieve excellent performances. For example, based on the proposed block-averaging method, the decoded Lena image has at least a 0.5 dB higher PSNR (under the same bit rate) and an eight-time faster decoding speed than the conventional fractal coding schemes that require iterations.     

Hybrid fractal image coding with quadtree-based progressive structure

A progressive structure which takes the quadtree depth into consideration is proposed for fractal image coding. Simulation results show that its image quality at different received data rates is better than that without considering the quadtree level. Then, a hybrid fractal image coding scheme based on traditional and no-search fractal image coding with the proposed progressive structure is suggested. The image quality and compression ratio can be controlled by a threshold, which makes it downward compatible to the no-search fractal image coding. Experimental results justify that the progressive performance of the proposed scheme is better than that of traditional fractal image coding.     

序列图像的分形编码

分形方法作为一种新兴的图像编码方法,有着压缩比高等独特的优点。但由于它也有着致命的缺点,即编码速度速度很慢,目前对于序列图像的分形编码的研究方兴未艾。文章介绍了两类主要的序列图像分形编码方法,并对其进行了展望。     

基于方向性零树小波的分形图像编码

该文阐述了分形图像方块编码在小波变换域内实现的原理,将零树概念扩展后与小波域的分形仿射变换相结合,提出一种基于方向性零树小波的分形图像编码方法。计算机模拟实验表明,在高压缩比时,其编码性能优于典型的基于四叉树分割的分形图像编码性能,接近于嵌入式零树小波编码(EZW)的性能。     

Still image coding based on vector quantization and fractalapproximation

In this paper, we propose a coding algorithm for still images using vector quantization (VQ) and fractal approximation, in which low-frequency components of an input image are approximated by VQ, and its residual is coded by fractal mapping. The conventional fractal coding algorithms indirectly used the gray patterns of an original image with contraction mapping, whereas the proposed fractal coding method employs an approximated and then decimated image as a domain pool and uses its gray patterns. Thus, the proposed algorithm utilizes fractal approximation without the constraint of contraction mapping. For approximation of an original image, we employ the discrete cosine transform (DCT) rather than conventional polynomial-based transforms. In addition, for variable blocksize segmentation, we use the fractal dimension of a block that represents the roughness of the gray surface of a region. Computer simulations with several test images show that the proposed method shows better performance than the conventional fractal coding methods for encoding still pictures.     

机动目标的逆合成孔径雷达成像原理与算法

对于非合作的机动目标,由于目标相对于雷达射线的姿态和转速难以测定,而且是时变的,因而给逆合成孔径雷达(ISAR)成像造成较大困难.本文讨论了这种情况下成像的一般原理,并对机动性不太大,散射点子回波多普勒变化满足一阶近似条件时,提出了实用算法.实测数据的处理结果说明新算法是可行的.