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fractal image compression using a fast affine transform and hierarchical classification scheme

VISUAL COMPUTER 2022年第11期38卷 3867-3880页

作者： Nandi, Utpal Vidyasagar Univ Dept Comp Sci Midnapore 721102 W Bengal India

fractal image compression is one of the efficient structure-based methods in applications where images are compressed only once but decoded several times due to its resolution-independent feature and fast reconstruction time. However, it has high computational complexity restricting practical use most of the time. Although several methods have been developed to speed up the compression process, these do not satisfy the compression time or the decoded image quality requirements. The affine transforms of image blocks used in fractal coding require a huge number of multiplications and additions and are very expensive in computation that may also slow down the compression process. This paper presents a novel fractal image compression using a fast affine transform and hierarchical classification scheme. The applied affine transform computation algorithm of image blocks uses relationships among neighboring pixels of transformed image block that significantly reduces the number of multiplication and addition operations. Then, this strategy with hierarchical classification and class-wise domain sorting is applied in fractal coding with quad-tree and horizontal vertical partitioning schemes to reduce compression time. Experimental results show that the quad-tree-based fractal coding with the proposed scheme can significantly speed up the compression process keeping image quality and compression ratio almost unchanged.

关键词： fractal image compression Affine transform Encoding time compression ratio image quality Iterated function system

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Parallel fractal image compression using quadtree partition with task and dynamic parallelism

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JOURNAL OF REAL-TIME image PROCESSING 2022年第2期19卷 391-402页

作者： Hernandez-Lopez, Francisco J. Muniz-Perez, Omar CONACYT Ctr Invest Matemat AC PCTY CIMAT Unidad Merida Merida 97302 Yucatan Mexico

fractal image compression is a lossy compression technique based on the iterative function system, which can be used to reduce the storage space and increase the speed of data transmission. The main disadvantage of fractal image compression is the high computational cost of the encoding step, compared with the popular image compression based on discrete cosine transform. The aim of this paper is the development of parallel implementations of fractal image compression using quadtree partition. We develop two parallel implementations: the first one uses task parallelism over a multi-core system and the second uses dynamic parallelism over a GPU architecture. We show performance comparisons of the parallel implementations using standard images to compare the capabilities of these parallel architectures. The proposed parallel implementations achieve speedups over the serial implementation of approximately 15x using the multi-core CPU and 25x using the GPU.

关键词： fractal image compression Quadtree Task parallelism Dynamic parallelism Multi-core GPU

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CUDA implementation of fractal image compression

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JOURNAL OF REAL-TIME image PROCESSING 2020年第5期17卷 1375-1387页

作者： Al Sideiri, Abir Alzeidi, Nasser Al Hammoshi, Mayyada Chauhan, Munesh Singh AlFarsi, Ghaliya Buraimi Univ Coll Dept Informat Technol Al Buraimi Oman Sultan Qaboos Univ Dept Comp Sci Muscat Oman Univ Tenaga Natl UniTen Dept Syst & Networks Kajang Malaysia Virginia Int Univ Sch Comp Informat Syst Fairfax VA USA Coll Appl Sci Dept Informat Technol Salalah Oman

fractal coding is a lossy image compression technique, which encodes the image in a way that would require less storage space using the self-similar nature of the image. The main drawback of fractal compression is the high encoding time. This is due to the hard task of finding all fractals during the partition step and the search for the best match of fractals. Lately, GPUs (Graphical Processing Unit) have been exploited to implement fractal image compression algorithms due to their high computational power. The prime aim of this paper is to design and implement a parallel version of the Fisher classification scheme using CUDA to exploit the computational power available in the GPUs. Fisher classification scheme is used to reduce the encoding time of fractal images by limiting the search for the best match of fractals. Encoding time, compression ratio and peak signal-to-noise ratio was used as metrics to assess the correctness and the performance of the developed algorithm. Eight images with different sizes (512 x 512, 1024 x 1024 and 2048 x 2048) have been used for the experiments. The conducted experiments showed that a speedup of 6.4 x was achieved in some images using NVIDIA GeForce GT 660 M GPU.

关键词： fractal image compression Quad-tree partitioning GPU Parallel processing CUDA

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Impact of Spatial Dynamic Search With Matching Threshold Strategy on fractal image compression Algorithm Performance: Study

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IEEE ACCESS 2020年 8卷 52687-52699页

作者： Saad, Abdul-Malik H. Y. Abdullah, Mohd Zaid Alduais, Nayef Abdulwahab Mohammed Sa'ad, Hisham Haider Yusef Univ Sains Malaysia Sch Elect & Elect Engn Nibong Tebal 14300 Malaysia Univ Tun Hussein Onn Malaysia Fac Comp Sci & Informat Technol FSKTM Parit Raja 86400 Malaysia Al Razi Univ Fac Comp Sci & IT Sanaa Yemen

fractal image compression (FIC) is a very popular technique in image compression applications due to its simplicity and superior performance. However, it has a major drawback, which is the long encoding time. This is due to the requirement of performing huge similarity search for encoding each small portion in the image. Thus, reducing the search time of FIC while keeping the quality of reconstructed images at acceptable level is still an active research topic. Therefore, this paper has focused on studying the search problem of the conventional full-search FIC algorithm and the impact of employing a spatial dynamic search technique instead with the matching threshold strategy. Unlike the conventional full-search method that is a spatially static where the search starts from a fixed position (normally from the top-left corner of the image to the bottom-right corner) regardless of the position of the range block being encoding, the idea of the dynamic search method is simple, but effective, and it is based on starting the search from the closest domain block to the range block that needs to be encoded. These two search schemes are tested under different matching threshold values, in which the search is terminated whenever a domain block with an acceptable matching level is found. To make the study comprehensive, the test is performed for different image sizes and types, range block and partitioning step sizes, and quantization levels. The experimental results show the significant impact of using the dynamic search method instead of the conventional search method specifically when the threshold is large. For the best encoding parameters, the improvement amount that can be achieved is near to 90 & x0025;in terms of search reduction and 1.6 dB PSNR in terms of image quality.

关键词： fractal image compression fast search method full search scheme

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Modified Bat Algorithm with Local Search for fractal image compression of Bitmap images 18

Modified Bat Algorithm with Local Search for Fractal Image C...

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18th International Conference on Cyberworlds (CW)

作者： Galvez, Akemi Iglesias, Andres Toho Univ Fac Sci Dept Informat Sci Funabashi Chiba Japan Univ Cantabria Dept Appl Math & Comp Sci Santander Spain

ISBN: (纸本)9781728122977

This paper introduces a new method for IFS fractal image compression of bitmap images. The method is based on the bat algorithm, a powerful swarm intelligence method for optimization. This algorithm is modified with two additional features: a new population model based on strong elitism and new random individuals, and the inclusion of mutation operators. The modified method is also coupled with a local search heuristics for further enhancement. An illustrative example is used to analyze the performance of this approach. Our experiments on a fractal image show that the method performs very well, being able to capture the underlying structure of the original image with good visual quality. We also compared our method with other alternative approaches in the literature and found that it outperforms all of them for the given example. However, the numerical results show that there is also room for further improvement. We conclude that the method is promising and can potentially become a very useful and effective technique for fractal image compression of bitmap images.

关键词： bitmap images fractal image compression iterated function systems collage theorem evolutionary computation swarm intelligence bat algorithm local search

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High-Speed fractal image compression Featuring Deep Data Pipelining Strategy

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IEEE ACCESS 2018年 6卷 71389-71403页

作者： Saad, Abdul-Malik H. Y. Abdullah, Mohd Z. Univ Sains Malaysia Sch Elect & Elect Engn Engn Campus Nibong Tebal 14300 Malaysia Univ Sains Malaysia Collaborat Microelect Design Excellence Ctr Engn Campus Nibong Tebal 14300 Malaysia

A new architecture based on deep data pipelining is proposed for implementing fractal compression of high-resolution images in real time. The general idea is to partition an image into overlapping range and domain blocks in which four range blocks constitute one domain block. In this way, two matching operations can be performed simultaneously using two processor units. Further reduction in the encoding time is achieved by exploiting the inherently high degree of correlation among pixels in the neighborhood areas and restricting the search in the neighboring blocks only. The design is synthesized on Altera Stratix IV field-programmable gate array and optimized at circuit level in order to achieve a high-speed implementation. The proposed architecture is evaluated in terms of the peak signal-to-noise ratio (PSNR), the runtime, the memory utilization, and the compression ratio (CR). Experimental results suggest that the proposed architecture is able to encode a 1024 x 1024 size image in 10.8 ms with PSNR and CR averaging at 27 dB and 34:1, respectively. Meanwhile, the energy dissipation is approximately 0.5 W which is comparable to the state-of-the-art fractal processors.

关键词： Digital circuits field programmable gate arrays fractal image compression parallel architectures pipeline processing

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Comparative analysis of edge-based fractal image compression using nearest neighbor technique in various frequency domains

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ALEXANDRIA ENGINEERING JOURNAL 2018年第3期57卷 1525-1533页

作者： Gupta, Richa Mehrotra, Deepti Tyagi, Rajesh Kumar Amity Univ Noida Uttar Pradesh India Krishna Inst Engn & Technol Ghaziabad Uttar Pradesh India

In this paper, edge based fractal image compression is proposed for various frequency domains. Range and domain blocks of similar edge property are mapped to lowest DCT coefficient in a vertical and horizontal direction into 2D coordinate System. The proposed algorithm is hybrid approaches which exercise fast Fourier transform (FFT), discrete cosine transform (DCT) and real DCT on edge based FIC. Range and domain block pool searching is proposed using k-nearest neighbor search method. Here dissimilarity or distance measure is used in K-NN search for domain and range block. Three frequency transform is used to compare the performance of edge based FIC for K-NN search strategies. The proposed algorithm focuses on image encoding time consumed in edge based FIC with minimal distortion in the resultant image. Proposed algorithm shows improvement in the quality of decoded image with same encoding time and compression ratio as compared to the existing algorithm. The quality of the decoded image was measured regarding PSNR. (C) 2017 Faculty of Engineering, Alexandria University. Production and hosting by Elsevier B.V.

关键词： fractal image compression Edge property Frequency domain Nearest neighbor DCT FFT

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An improved fractal image compression using wolf pack algorithm

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JOURNAL OF EXPERIMENTAL & THEORETICAL ARTIFICIAL INTELLIGENCE 2018年第3期30卷 429-439页

作者： Menassel, R. Nini, B. Mekhaznia, T. Badji Mokhtar Univ Dept Comp Sci Annaba Algeria Larbi Ben MHidi Univ Dept Comp Sci Oum El Boughi Algeria Larbi Tebessi Univ Dept Comp Sci Tebessa Algeria

The fractal image compression is a recent tool for encoding natural images. It builds on the local self-similarities and the generation of copies of blocks based on mathematical transformations. The technique seems interesting in both theory and application but have a drawback renders in real-time usage due to the high resource requirement when encoding big data. By another way, heuristics algorithms represent a set of approaches used to solve hard optimisation tasks with rational resources consumption. They are characterised with their fast convergence and reducing of research complexity. The purpose of this paper is to provide, and for the first time, more detailed study about the Wolf Pack Algorithm for the fractal image compression. The whole image is considered as a space search where this space is divided on blocks, the scooting wolves explore the space to find other smaller block which have a similarity with based on its parameters. Scooting wolfs perused the whole space a selected the blocks with the best fitness. The process will be stopped after a fixed number of iterations or if no improvement in lead wolf solution. Results show that compared with the exhaustive search method, the proposed method greatly reduced the encoding time and obtained a rather best compression ratio. The performed experiments showed its effectiveness in the resolution of such problem. Moreover, a brief comparison with the different methods establishes this advantage.

关键词： fractal image compression bio-inspired heuristics and wolf pack algorithm

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Enhancing fractal image compression speed using local features for reducing search space

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PATTERN ANALYSIS AND APPLICATIONS 2017年第4期20卷 1119-1128页

作者： Jaferzadeh, Keyvan Moon, Inkyu Gholami, Samaneh Chosun Univ Dept Comp Engn 309 Pilmun Daero Gwangju 501759 South Korea

The encoding step in full-search fractal image compression is time intensive because a sequential search through a massive domain pool has to be executed to find the best-matched domain for every range block. To afford a fair encoding time, immaterial domain-range block comparisons should be prevented. In this paper, a new local binary feature resemble to local binary patterns method is introduced. This single local feature is robust to noise and can exploit the general structure of the block. Concerning similarity between range-domain blocks, a criterion is allocated dynamically by measuring the pixel diversity among the range block pixels. To avoid redundant calculations, the distance of the general pattern is assessed by the Hamming distance utilizing a pre-computed table. Experimental results show that the presented approach can make FIC a lot faster as opposed to the full-search method and outperform some other identical methods while preserving the quality of the decoded images. Indeed, the proposed method can be utilized inside identical applications that want a specific block size or blocks comparing.

关键词： fractal image compression Local features Hamming distance Local binary pattern Adaptive thresholding

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Polynomial Based fractal image compression using DWT Screening 4

Polynomial Based Fractal Image Compression using DWT Screeni...

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4th IEEE International Conference on Signal Processing, Computing and Control (ISPCC)

作者： Chauhan, Pradeep Gupta, Bhumika Ballabh, Upendra GBPEC Dept Comp Sci & Engn Pauri Ghurdauri India

ISBN: (纸本)9781509058389

Picture pressure is a fundamental innovation in sight and sound and advanced correspondence fields. fractal picture pressure is a potential picture pressure plot because of its potential high pressure proportion, quick decompression and multi determination properties. fractal picture pressure uses the presence of self symmetry of pictures. It is an lopsided method which take more time in compression than decompressing an image. The intellection is to do utmost of the work during compression. However the high computational unpredictability of fractal picture encoding incredibly limits its applications. A few procedures and enhancements have been recommended to accelerate the fractal picture pressure on polynomial insertion. This paper introduces an audit of the methods such as DWT and CLAHE distributed for speedier fractal picture compression using polynomial introduction with pre pack. Preliminary results shows a quite improvement in compression ratio, mean square blunder and the pinnacle flag to clamor proportion (PSNR).

关键词： image compression fractal image compression Pre-processing(DWT Sharpening) polynomial interpolation pre-compress image portioning

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