Genetic adaptive coding optimization applied to fractal image compression

This paper presents a fractal image compression method that utilized a genetic optimization algorithm for optimal domain block selection. The technique successfully addresses the problem of finding an optimal domain block pool for a given range partition, one of the most important issues in fractal image compression. This technique utilizes a genetic optimization algorithm that starts with a source image and generates both a random range partition and a random set of candidate domain blocks for each element of the range partition. Each member of the candidate domain block set was mapped to the corresponding element of the range partition. It was subsequently tested via a quantitative objective function, ranked using a linear fitness scheme and modified, as required, using crossover and mutation operators. This evolutionary process converged to produce an optimal iterated function system (IFS) representation of the source image within a few generations in a robust and efficient manner. © 1999 John Wiley & Sons, Inc. Int J Imaging Syst Technol 10, 369–378, 1999     

Adaptive fractal image coding in subband domain

Abstract

In this paper, we propose and evaluate a method for fractal image coding in the subband domain. The subband decomposition scheme acts as a classifier, which can efficiently reduce encoding time. The proposed fractal image coding scheme is an adaptive one. The adaptability is based on the variance of each subband. At each subband, the scheme adaptively sets the map block size that should be encoded. In addition, the domain blocks are adaptively restricted to the neighborhood of their respective range block. Simulation results show that good picture quality of the coded image is obtained at 0.370 bpp. It also indicates that such an adaptive scheme makes a better trade‐off between the required bit rate and picture quality than a fixed size one. Moreover, the adaptive shceme can save a large amount of time.     

基于形态学算子的分形图像编码

本文提出了一种基于数学形态学算子的分形图像编码方法。首先用ＡＭＳＳ算子对原图像进行作用，得到的结果作为Ｄｏｍａｉｎ Ｐｏｏｌ。在此基础上，再对图像进行分割、搜索并获得仿射变换族，形成相应的ＰＩＦＳ。本文对该方法下的压缩变换、解码算法、Ｃｏｌｌａｇｅ定理等相关的理论进行了讨论。在编码过程中，采用ＡＭＳＳ图像作为Ｄｏｍａｉｎ Ｐｏｏｌ的意义在于，ＡＭＳＳ算子拓宽了Ｄｏｍａｉｎ Ｐｏｏｌ的边缘范围，使经     

Enhanced three-dimensional discrete cosine transform based compression method for integral images by adaptive three-dimensional block construction

In this paper, we propose an efficient compression method for integral images based on three-dimensional discrete cosine transform (3D-DCT). Even though the existing 3D-DCT based techniques are efficient, they may not be optimized to the characteristics of integral images, such as applying a fixed size block construction and a fixed scanning in placing 2D blocks to construct a 3D block. Therefore, we propose a variable size block construction and a scanning method adaptive to characteristics of integral images, which are realized by adaptive 3D block modes. Experimental results show that the proposed method gives significant improvement in coding efficiency. In particular, at the high bit rates, the proposed method is more improved, since overhead bits for signaling of the 3D block modes take a smaller part of the total bits.     

A new modified fast fractal image compression algorithm

Abstract

In this paper, a new fractal image compression algorithm is proposed, in which the time of the encoding process is considerably reduced. The algorithm exploits a domain pool reduction approach, along with the use of innovative predefined values for contrast scaling factor, S, instead of searching it across. Only the domain blocks with entropy greater than a threshold are considered to belong to the domain pool. The algorithm has been tested for some well-known images and the results have been compared with the state-of-the-art algorithms. The experiments show that our proposed algorithm has considerably lower encoding time than the other algorithms giving approximately the same quality for the encoded images.     

Volumetric medical image compression using inter-slice correlation switched prediction approach

With the advancement in medical data acquisition and telemedicine systems, image compression has become an important tool for image handling, as the tremendous amount of data generated in medical field needs to be stored and transmitted effectively. Volumetric MRI and CT images comprise a set of image slices that are correlated to each other. The prediction of the pixels in a slice depends not only upon the spatial information of the slice, but also the inter-slice information to achieve compression. This article proposes an inter-slice correlation switched predictor (ICSP) with block adaptive arithmetic encoding (BAAE) technique for 3D medical image data. The proposed ICSP exploits both inter-slice and intra-slice redundancies from the volumetric images efficiently. Novelty of the proposed technique is in selecting the correlation coefficient threshold (T_ϒ) for switching of ICSP. Resolution independent gradient edge detector (RIGED) at optimal prediction threshold value is proposed for intra-slice prediction. Use of RIGED, which is modality and resolution independent, brings the novelty and improved performance for 3D prediction of volumetric images. BAAE is employed for encoding of prediction error image to resulting in higher compression efficiency. The proposed technique is also extended for higher bit depth volumetric medical images (16-bit depth) presenting significant compression gain of 3D images. The performance of the proposed technique is compared with the state-of-the art techniques in terms of bits per pixel (BPP) for 8-bit depth and was found to be 31.21%, 27.55%, 21.89%, and 2.39% better than the JPEG-2000, CALIC, JPEG-LS, M-CALIC, and 3D-CALIC respectively. The proposed technique is 11.86%, 8.56%, 7.97%, 6.80%, and 4.86% better than the M-CALIC, 3D CALIC, JPEG-2000, JPEG-LS and CALIC respectively for 16-bit depth image datasets. The average value of compression ratio for 8-bit and 16-bit image dataset is obtained as 3.70 and 3.11 respectively by the proposed technique.     

Lossless color medical image compression using adaptive block‐based encoding for human computed tomographic images

The advancement in medical imaging systems such as computed tomography (CT), magnetic resonance imaging (MRI), positron emitted tomography (PET), and computed radiography (CR) produces huge amount of volumetric images about various anatomical structure of human body. There exists a need for lossless compression of these images for storage and communication purposes. The major issue in medical image is the sequence of operations to be performed for compression and decompression should not degrade the original quality of the image, it should be compressed loss lessly. In this article, we proposed a lossless method of volumetric medical image compression and decompression using adaptive block‐based encoding technique. The algorithm is tested for different sets of CT color images using Matlab. The Digital Imaging and Communications in Medicine (DICOM) images are compressed using the proposed algorithm and stored as DICOM formatted images. The inverse process of adaptive block‐based algorithm is used to reconstruct the original image information loss lessly from the compressed DICOM files. We present the simulation results for large set of human color CT images to produce a comparative analysis of the proposed methodology with block‐based compression, and JPEG2000 lossless image compression technique. This article finally proves the proposed methodology gives better compression ratio than block‐based coding and computationally better than JPEG 2000 coding. © 2013 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 23, 227–234, 2013     

Colour image coding scheme using absolute moment block truncation coding and block prediction technique

Abstract

A predictive colour image compression scheme based on absolute moment block truncation coding is proposed. In this scheme, the high correlations among neighbouring image blocks are exploited by using the similar block prediction technique. In addition, the bit plane omission technique and the coding of quantisation levels are used to cut down the storage cost of smooth blocks and complex blocks respectively. According to the experimental results, the proposed scheme provides better performance than the comparative schemes based on block truncation coding. It provides better image qualities of compressed images at low bit rates. Meanwhile, it consumes very little computational cost. In other words, the proposed scheme is quite suitable for real time multimedia applications.     

Dimensional scalable lossless compression of MRI images using haar wavelet lifting scheme with EBCOT

Modern medical imaging requires storage of large quantities of digitized clinical data. To provide high bandwidth and to reduce the storage space, a medical image must be compressed before transmission. One of the best image compression techniques is using the Haar wavelet transform. The method of discrete cosine transform (DCT) is chosen to be the preprocessing scheme to identify the image frequency information and has excellent energy compaction property. The block coding algorithm uses a wavelet transform to generate the sub band samples, which can be quantized and coded. It is more robust to errors than many other wavelet‐based schemes. In this article, simulations are carried out on different medical Images and it demonstrates the performance in terms of peak signal to noise ratio (PSNR) & bits per pixel (BPP). Our proposed method is found to preserve information fidelity while reducing the amount of data. © 2014 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 24, 175–181, 2014     

基于神经网络和方差的快速分形图像编码算法

为克服快速分形图像编码带来的解码图像质量下降问题,提出了一种神经网络与方差混合编码的快速分形图像编码算法.该算法结合图像子块复杂度与方差值的对应关系,根据每个区块的方差值大小选择适当的映射编码方法,即对于方差值相对小的区块采用方差编码以提高编码速度,对于方差值相对大的区块采用神经网络编码以提高编码质量.该算法可以较好地修正传统分形编码中由于自仿射映射结构限制所带来的解码质量偏低的问题,在大幅提高编码速度的同时,很好地保持了图像的编码质量.实验结果表明,该算法对比基本分形编码算法可以加速24倍,解码图像的质量对比方差快速分形编码算法有1.1dB的提高.同时,该算法的硬件实现比较容易,非常贴近实用化.     

Optical flow-based motion compensation algorithm for very low-bit-rate video coding

In this article, we propose an efficient compression algorithm for very low-bit-rate video applications. The algorithm is based on (a) an optical-flow motion estimation to achieve more accurate motion prediction fields; (b) discrete cosine transformation (DCT) coding of the motion vectors from the optical-flow estimation to reduce the motion overheads; and (c) an adaptive threshold technique to match optical flow motion prediction and minimize the residual errors. Unlike the classic block-matching based DCT video coding schemes in MPEG-1/2 and H.261/3, the proposed algorithm uses optical flow for motion compensation and the DCT is applied to the optical flow field instead of predictive errors. Thresholding techniques are used to treat different regions to complement optical flow technique and to efficiently code residual data. While maintaining a comparable peak signal-to-noise ratio (PSNR) and computational complexity with that of ITU-T H.263/TMN5, the reconstructed video frames of the proposed coder are free of annoying blocking artifacts, and hence visually much more pleasant. The computer simulation are conducted to show the feasibility and effectiveness of the algorithm. Results at 11 kbps are presented which can be used for videophone applications in the existing public switched telephone network (PSTN). © 1998 John Wiley & Sons, Inc. Int J Imaging Syst Technol, 9, 230–237, 1998     

SVD-based digital image watermarking using adaptive generated watermark

In this paper, an evolutionary-based algorithm for digital image watermarking is proposed. Robustness and imperceptibility are two important properties of digital image watermarking which conflict with each other. A singular value decomposition (SVD)-based intelligent algorithm is applied to make a trade-off between robustness and imperceptibility. In the proposed algorithm, first, the original image is divided into 8×8 blocks. Then some special blocks are transformed into discrete cosine transform (DCT) domain. SVD decomposition of DCT coefficients of special blocks is the next stage of the method. Finally, a binary watermark image is embedded into the singular values by a quantisation method. The major property of the proposed method is the generation of a binary watermark image using genetic algorithm to solve the optimisation problem between robustness and imperceptibility. So the watermark could be variable and image adaptive. The simulation results show improvement in robustness of the proposed method against several attacks such as noise contamination, filtering, joint photographic experts group (JPEG) compression and some geometrical attacks like cropping, rotation and rescaling in comparison with a recently similar existing work.     

分形图像压缩方法研究的新进展

分形图像压缩是一种利用迭代函数系统理论(IFS)、基于自相似特征的有损编码方法。它以其高压缩比的潜在性能而在近年来倍受重视，但目前实现自动IFS编码仍有相当难度，该领域仍存在许多问题亟待解决。笔者对分形图像压缩的理论基础、自动分形图像压缩的实现以及分形图像序列压缩等进行了全面的综述，介绍了各种具有代表性的改进算法，阐明了各个算法的原理和特点，最后对目前研究中存在的问题及可能的对策和研究方向进行了讨论。     

基于图像特征的分形压缩方法

介绍了分形图像压缩的理论基础和基本编码思想。设计了一种基于图像特征的分形压缩编码方法,该方法在分析图像本身的结构特征的同时,充分利用了人眼对灰度的敏感程度随背景变化而变化的特点。在综合考虑图像的平均灰度与图像块的灰度阶差和图像块灰度方差的前提下,将图像块分为普通块和特征块,并对不同的图像块动态地改变搜索范围、匹配精度及压缩仿射变换因子,从而提高压缩效率。     

Wavelet‐based adaptive vector quantization for still‐image coding

Wavelet transform coding (WTC) with vector quantization (VQ) has been shown to be efficient in the application of image compression. An adaptive vector quantization coding scheme with the Gold‐Washing dynamic codebook‐refining mechanism in the wavelet domain, called symmetric wavelet transform‐based adaptive vector quantization (SWT‐GW‐AVQ), is proposed for still‐image coding in this article. The experimental results show that the GW codebook‐refining mechanism working in the wavelet domain rather than the spatial domain is very efficient, and the SWT‐GW‐AVQ coding scheme may improve the peak signal‐to‐noise ratio (PSNR) of the reconstructed images with a lower encoding time. © 2002 Wiley Periodicals, Inc. Int J Imaging Syst Technol 12, 166–174, 2002; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/ima.10024     

Causal fractal compression of video sequences using matching pursuit

In this article, a new video coding system is proposed which takes advantage of both intrascale and interscale similarities present in video sequences. Each block in every frame is approximated with a linear combination of members of an adaptive library of blocks constructed for that block. This library is made up of some fixed blocks (e.g., DCT basis blocks) and some adaptive blocks. The adaptive library blocks are blocks of the same size or larger blocks that are shrunk, taken from the previous frame. For each block in every frame, a rate-distortion optimized fully orthogonal matching pursuit algorithm is used to determine how many and which ones of the members of the library constructed for that block should be selected and linearly combined to approximate the block most efficiently in terms of bit rate and rms error. Simulation results on sample gray-scale video sequence “Miss America” suggests that this method has promising coding performance in terms of PSNR and bit rate,especially compared to other published fractal-based video compression methods. © 1998 John Wiley & Sons, Inc. Int J Imaging Syst Technol, 9, 305–319, 1998     

改进的分形灰度图像压缩算法的研究

目的为了解决传统的分形图像压缩算法计算量大和实时性差的问题,提出一种改进的分形灰度图像压缩算法。方法算法首先基于Gabor变换提取图像块的纹理特征,然后基于K-means算法对R块和D块以纹理作为特征进行聚类处理,并仅对同一类别的R块和D块进行匹配操作。结果在候选块池的构造过程中,文中提出了8种等距变换的简化算法。结论文中方法能够在加快分形压缩速度的同时,较好地保证重建图像的视觉效果,具有较好的鲁棒性。     

An Algorithm to Reduce Compression Ratio in Multimedia Applications

In recent years, it has been evident that internet is the most effective means of transmitting information in the form of documents, photographs, or videos around the world. The purpose of an image compression method is to encode a picture with fewer bits while retaining the decompressed image’s visual quality. During transmission, this massive data necessitates a lot of channel space. In order to overcome this problem, an effective visual compression approach is required to resize this large amount of data. This work is based on lossy image compression and is offered for static color images. The quantization procedure determines the compressed data quality characteristics. The images are converted from RGB to International Commission on Illumination CIE La^*b^*; and YCbCr color spaces before being used. In the transform domain, the color planes are encoded using the proposed quantization matrix. To improve the efficiency and quality of the compressed image, the standard quantization matrix is updated with the respective image block. We used seven discrete orthogonal transforms, including five variations of the Complex Hadamard Transform, Discrete Fourier Transform and Discrete Cosine Transform, as well as thresholding, quantization, de-quantization and inverse discrete orthogonal transforms with CIE La^*b^*; and YCbCr to RGB conversion. Peak to signal noise ratio, signal to noise ratio, picture similarity index and compression ratio are all used to assess the quality of compressed images. With the relevant transforms, the image size and bits per pixel are also explored. Using the (n, n) block of transform, adaptive scanning is used to acquire the best feasible compression ratio. Because of these characteristics, multimedia systems and services have a wide range of possible applications.     

基于归一化的全息水印技术

提出了一种结合了归一化技术和全息技术的数字水印技术。首先,利用归一化技术对图像作归一化运算,同时利用全息技术将水印二值图处理为全息图;其次,取归一化后图像分块离散余弦变换的中频系数,对中频系数所组成的矩阵作离散小波变换;最后将全息图嵌入到离散小波变换的低频分量中。由于图像归一化技术具有抗仿射变换的性能,同时全息技术具有很强的抗裁切的性能,所以此数字水印技术具有很强的抗仿射变换的性能,可以广泛的用于数字作品的版权保护。     

基于二值离散运算的自适应数字图像水印算法

论文提出了一种在小波变换域内基于二值离散运算的自适应数字图像水印算法.算法利用人眼视觉掩盖特性,根据要嵌入的伪随机数水印长度自适应地选择原始图像小波逼近子图中纹理信息丰富的图像子块,通过对这些图像子块系数的二值离散修改实现水印的嵌入,水印检测无需原始图像.由于水印的嵌入与检测是基于二值离散运算,所嵌入的水印具有很理想的鲁棒性,能免疫于常规图像处理方法的有限攻击.同时,嵌入的水印具有理想的隐蔽效果,完全满足水印不可觉察性要求.