A survey of parallel algorithms for fractal image compression

This paper presents a short survey of the key research work that has been undertaken in the application of parallel algorithms for Fractal image compression. The interest in fractal image compression techniques stems from their ability to achieve high compression ratios whilst maintaining a very high quality in the reconstructed image. The main drawback of this compression method is the very high computational cost that is associated with the encoding phase. Consequently, there has been significant interest in exploiting parallel computing architectures in order to speed up this phase, whilst still maintaining the advantageous features of the approach. This paper presents a brief introduction to fractal image compression, including the iterated function system theory upon which it is based, and then reviews the different techniques that have been, and can be, applied in order to parallelize the compression algorithm

Quadtree partitioning scheme of color image based

Image segmentation is an essential complementary process in digital image processing and computer vision, but mostly utilizes simple segmentation techniques, such as fixed partitioning scheme and global thresholding techniques due to their simplicity and popularity, in spite of their inefficiency. This paper introduces a new split-merge segmentation process for a quadtree scheme of colour images, based on exploiting the spatial and spectral information embedded within the bands and between bands, respectively. The results show that this technique is efficient in terms of quality of segmentation and time, which can be used in standard techniques as alternative to a fixed partitioning scheme

A Review on Block Matching Motion Estimation and Automata Theory based Approaches for Fractal Coding

Fractal compression is the lossy compression technique in the field of gray/color image and video compression. It gives high compression ratio, better image quality with fast decoding time but improvement in encoding time is a challenge. This review paper/article presents the analysis of most significant existing approaches in the field of fractal based gray/color images and video compression, different block matching motion estimation approaches for finding out the motion vectors in a frame based on inter-frame coding and intra-frame coding i.e. individual frame coding and automata theory based coding approaches to represent an image/sequence of images. Though different review papers exist related to fractal coding, this paper is different in many sense. One can develop the new shape pattern for motion estimation and modify the existing block matching motion estimation with automata coding to explore the fractal compression technique with specific focus on reducing the encoding time and achieving better image/video reconstruction quality. This paper is useful for the beginners in the domain of video compression

Kompresi Fractal dengan Metode Partisi Adaptive Quadtree

Kompresi fractal merupakan teknik yang tergolong baru dalam sejarah kompresi citra. Dengan memanfa-atkan kesamaan bentuk dengan bagian yang lebih kecil pada citra, metode kompresi  fractal diperkenalkan. Dalam kompresi fractal, bagian kecil yang memiliki  suatu kemiripan dengan bagian yang lebih besar pada citra akan dilakukan transformasi scan berulang-ulang  sehingga membentuk bagian besar tersebut. Proses ini disebut juga dengan iterated function system. Penelitian ini membahas mengenai pengompresan  citra hitam putih menggunakan metode partisi adaptive quadtree. Maksud dari metode ini adalah compresi fractal yang skema partisinya menggunakan skema partisi quadtree  dengan threshold yang berubah­ubah  (adaptive  threshold).  Penelitian  ini  merancang  skema  partisi  quadtree menggunakan adaptive threshold untuk lebih mengoptimalkan hasil suatu kompresi citra baik dari segi kualitas, rasio, dan waktu pengompresan. Pada skema partisi standar. suatu citra dipartisi menjadi bagian-bagian berbentuk persegi dengan ukuran yang sama. Partisi jenis ini memiliki kelemahan utama yaitu terpartisinya bagian citra yang sebenarnya memiliki tingkat kompleksitas rendah. Hal ini sangat tidak efisien dikarenakan  pemborosan bit yang terjadi untuk merekam koefisien dari bagian-bagian tersebut untuk pengompresan sehingga menyebabkan ukuran file menjadi besar. Skema partisi quadtree memungkinkan  untuk mempartisi citra menjadi bagian-bagian yang memiliki ukuran yang berbeda sesuai dengan tingkat kompleksitas bagian  tersebut  berdasarkan  threshold  yang  sudah  ditetapkan  sebelumny

Fractal compression and analysis on remotely sensed imagery

Remote sensing images contain huge amount of geographical information and reflect the complexity of geographical features and spatial structures. As the means of observing and describing geographical phenomena, the rapid development of remote sensing has provided an enormous amount of geographical information. The massive information is very useful in a variety of applications but the sheer bulk of this information has increased beyond what can be analyzed and used efficiently and effectively. This uneven increase in the technologies of gathering and analyzing information has created difficulties in its storage, transfer, and processing. Fractal geometry provides a means of describing and analyzing the complexity of different geographical features in remotely sensed images. It also provides a more powerful tool to compress the remote sensing data than traditional methods. This study suggests, for the first time, the implementation of this usage of fractals to remotely sensed images. In this study, based on fractal concepts, compression and decompression algorithms were developed and applied to Landsat TM images of eight study areas with different land cover types; the fidelity and efficiency of the algorithms and their relationship with the spatial complexity of the images were evaluated. Three research hypotheses were tested and the fractal compression was compared with two commonly used compression methods, JPEG and WinZip. The effects of spatial complexity and pixel resolution on the compression rate were also examined. The results from this study show that the fractal compression method has higher compression rate than JPEG and WinZip. As expected, higher compression rates were obtained from images of lower complexity and from images of lower spatial resolution (larger pixel size). This study shows that in addition to the fractal’s use in measuring, describing, and simulating the roughness of landscapes in geography, fractal techniques were useful in remotely sensed image compression. Moreover, the compression technique can be seen as a new method of measuring the diverse landscapes and geographical features. As such, this study has introduced a new and advantageous passageway for fractal applications and their important applications in remote sensing

Energy efficient hardware acceleration of multimedia processing tools

The world of mobile devices is experiencing an ongoing trend of feature enhancement and generalpurpose multimedia platform convergence. This trend poses many grand challenges, the most pressing being their limited battery life as a consequence of delivering computationally demanding features. The envisaged mobile application features can be considered to be accelerated by a set of underpinning hardware blocks Based on the survey that this thesis presents on modem video compression standards and their associated enabling technologies, it is concluded that tight energy and throughput constraints can still be effectively tackled at algorithmic level in order to design re-usable optimised hardware acceleration cores. To prove these conclusions, the work m this thesis is focused on two of the basic enabling technologies that support mobile video applications, namely the Shape Adaptive Discrete Cosine Transform (SA-DCT) and its inverse, the SA-IDCT. The hardware architectures presented in this work have been designed with energy efficiency in mind. This goal is achieved by employing high level techniques such as redundant computation elimination, parallelism and low switching computation structures. Both architectures compare favourably against the relevant pnor art in the literature. The SA-DCT/IDCT technologies are instances of a more general computation - namely, both are Constant Matrix Multiplication (CMM) operations. Thus, this thesis also proposes an algorithm for the efficient hardware design of any general CMM-based enabling technology. The proposed algorithm leverages the effective solution search capability of genetic programming. A bonus feature of the proposed modelling approach is that it is further amenable to hardware acceleration. Another bonus feature is an early exit mechanism that achieves large search space reductions .Results show an improvement on state of the art algorithms with future potential for even greater savings

Adaptive Fractal and Wavelet Image Denoising

The need for image enhancement and restoration is encountered in many practical applications. For instance, distortion due to additive white Gaussian noise (AWGN) can be caused by poor quality image acquisition, images observed in a noisy environment or noise inherent in communication channels. In this thesis, image denoising is investigated. After reviewing standard image denoising methods as applied in the spatial, frequency and wavelet domains of the noisy image, the thesis embarks on the endeavor of developing and experimenting with new image denoising methods based on fractal and wavelet transforms. In particular, three new image denoising methods are proposed: context-based wavelet thresholding, predictive fractal image denoising and fractal-wavelet image denoising. The proposed context-based thresholding strategy adopts localized hard and soft thresholding operators which take in consideration the content of an immediate neighborhood of a wavelet coefficient before thresholding it. The two fractal-based predictive schemes are based on a simple yet effective algorithm for estimating the fractal code of the original noise-free image from the noisy one. From this predicted code, one can then reconstruct a fractally denoised estimate of the original image. This fractal-based denoising algorithm can be applied in the pixel and the wavelet domains of the noisy image using standard fractal and fractal-wavelet schemes, respectively. Furthermore, the cycle spinning idea was implemented in order to enhance the quality of the fractally denoised estimates. Experimental results show that the proposed image denoising methods are competitive, or sometimes even compare favorably with the existing image denoising techniques reviewed in the thesis. This work broadens the application scope of fractal transforms, which have been used mainly for image coding and compression purposes

Fractal Image Compression with Region-Based Functionality

c ○ 2002 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE