An edge property-based neighborhood region search strategy for fractal image compression

Lin, Yih-Lon; Ming-sheng, WU

doi:10.1016/j.camwa.2011.05.011

Cited by 23 publications

(11 citation statements)

References 14 publications

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“…Truong et al proposed a new search strategy based on spatial correlation of images [30]. Lin et al implemented a neighborhood search by utilizing a phenomenon that similarly edge-shaped blocks are concentrated in certain regions [31]. Wang et al calculated and sorted the standard deviation of domain blocks.…”

Section: Fractal Image Compressionmentioning

confidence: 99%

Parallel Fractal Compression Method for Big Video Data

et al. 2018

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With the development of technologies such as multimedia technology and information technology, a great deal of video data is generated every day. However, storing and transmitting big video data requires a large quantity of storage space and network bandwidth because of its large scale. Therefore, the compression method of big video data has become a challenging research topic at present. Performance of existing content-based video sequence compression method is difficult to be effectively improved. Therefore, in this paper, we present a fractal-based parallel compression method without content for big video data. First of all, in order to reduce computational complexity, a video sequence is divided into several fragments according to the spatial and temporal similarity. Secondly, domain and range blocks are classified based on the color similarity feature to reduce computational complexity in each video fragment. Meanwhile, a fractal compression method is deployed in a SIMD parallel environment to reduce compression time and improve the compression ratio. Finally, experimental results show that the proposed method not only improves the quality of the recovered image but also improves the compression speed by compared with existing compression algorithms.

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Section: Fractal Image Compressionmentioning

confidence: 99%

Parallel Fractal Compression Method for Big Video Data

et al. 2018

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“…It reduces the affine redundancy existing in various parts of images by using a self -similarity feature which can give high compression ratio and fast decompression [2,3]. Lin [4] described a frequency domain based image coding method for best matched solution. Video information is characterized by its large storage requirement and it is also difficult to transmit raw video data efficiently.…”

Section: Introductionmentioning

confidence: 99%

Fast Quadtree Based Normalized Cross Correlation Method for Fractal Video Compression using FFT

Chaudhari¹,

Dhok²

2016

Journal of Electrical Engineering and Technology

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-In order to achieve fast computational speed with good visual quality of output video, we propose a frequency domain based new fractal video compression scheme. Normalized cross correlation is used to find the structural self similar domain block for the input range block. To increase the searching speed, cross correlation is implemented in the frequency domain using FFT with one computational operation for all the domain blocks instead of individual block wise calculations. The encoding time is further minimized by applying rotation and reflection DFT properties to the IFFT of zero padded range blocks. The energy of overlap small size domain blocks is pre-computed for the entire reference frame and retaining the energies of the overlapped search window portion of previous adjacent block. Quadtree decompositions are obtained by using domain block motion compensated prediction error as a threshold to control the further partitions of the block. It provides a better level of adaption to the scene contents than fixed block size approach. The result shows that, on average, the proposed method can raise the encoding speed by 48.8 % and 90 % higher than NHEXS and CPM/NCIM algorithms respectively. The compression ratio and PSNR of the proposed method is increased by 15.41 and 0.89 dB higher than that of NHEXS on average. For low bit rate videos, the proposed algorithm achieve the high compression ratio above 120 with more than 31 dB PSNR.

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“…Lossy compression can be reconstructed only by the approximation of the original one, the reconstructed image is similar to the original one, but it is not the exact copy. Lossy compression can get higher ratio compare to lossless compression [3].…”

Section: Introductionmentioning

confidence: 99%

Research of Fractal Compression Algorithm Taking Details in Consideration in Agriculture Plant Disease and Insect Pests Image

Deng¹,

Liu²,

Fu³

2016

Computer and Computing Technologies in Agriculture IX

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Agriculture plant disease and insect pests is varied and tremendously harmful, so experts are needed to diagnose. But experts can't have the energy and time to the field for the majority of farmers to guide, they can only get the image through remote. However, agriculture plant disease and insect pests image is rich in detail，while transmission bandwidth and storage is limited, it is necessary to compress image to make sure of image quality. This paper proposes an improved method based on Jacquin theory to reduce coding time. Encoded sub block is classified into detailed block and non-detailed block，so we can reduce the encoding time.Experimental results show that, for the agriculture plant disease and insect pests image which is rich in detail, the number of encoded blocks reduces to 31.45% and the encoding time reduces to 32.9% of the original one.

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An edge property-based neighborhood region search strategy for fractal image compression

Cited by 23 publications

References 14 publications

Parallel Fractal Compression Method for Big Video Data

Parallel Fractal Compression Method for Big Video Data

Fast Quadtree Based Normalized Cross Correlation Method for Fractal Video Compression using FFT

Research of Fractal Compression Algorithm Taking Details in Consideration in Agriculture Plant Disease and Insect Pests Image

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