Object-based stereo video compression using fractals and shape-adaptive DCT

Belloulata, Kamel; Belalia, Amina; Zhu, Shiping

doi:10.1016/j.aeue.2014.02.011

Cited by 24 publications

(10 citation statements)

References 18 publications

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“…As a development of single wavelet, multi-wavelet has such excellent properties as symmetry, orthogonality, short support and second-order vanishing moments, therefore, it has the advantages over single wavelet in the image processing and it can provide a more accurate analysis method [4,5]. Based on the research in the relevant literature, this paper investigates the integrated method by introducing the multi-wavelet transform and integrating the separate advantages of wavelet coding and fractal coding.…”

Section: A Fractal Image Compression Methods Based On Multi-wavelet (Ymentioning

confidence: 99%

A Fractal Image Compression Method Based on Multi-Wavelet

2015

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How to effectively store and transmit such multi-media files as image and video has become a research hotspot. The traditional compression algorithms have a relatively low compression ratio and bad quality of decoded image, at present, the fractal image compression method with a higher compression Keywords: multi-wavelet, fractal theory, image compressionCopyright © 2015 Universitas Ahmad Dahlan. All rights reserved. IntroductionThe image compression technology is a technique to use as few bits as possible to express the image signal from the information source to loweras much resource consumption such as the frequency bandwidth occupied by the image data, the storage space and the transmission time as possible for the sake of the transmission and storage of image signal. In fact, there exists strong correlation between the image pixels and such correlation has brought plenty of redundant information to the image, which makes image compression possible [1]. As a new image compression algorithm developed in the past decade, fractal image compression method attaches great importance to digging the self-similarity in most images and realizes the coding of an image with complicated visual characteristics on the surface via limited coefficients by using the iterated function system and some simple iteration rules. By using these rules, the decoder can realize the iterative decoding of the original image, therefore, the fractal image compression algorithm can achieve a highercompression ratio than other image compression algorithms [2].However, the fractal image compression algorithm still has many problems in both theory and application. For example, during the compression, the computation is too complicated, the compression time is too long, the convergence process is difficult to predict and control and there is block effect in the high compression ratio. The biggest problem of the basic fractal image compression algorithm is that its high compression ratio is at the cost of the huge coding time. It requires global search on all the domain blocks for every R block to search for the optimal matching domain block, therefore, the coding phase demands much computation time [3]. It usually takes hours to code a common 256x256 image, which greatly affects the practicability of fractal image compression, therefore, numerous improved algorithms are trying to find a quick way to accelerate the coding speed,and nevertheless, the increased coding speed comes together with the decreased image-reproduction quality. Tosurmount the shortcomings of the traditional fractal image compression algorithms, this paper make some research on the coding method integrating fractal and wavelet transform. In essence, wavelet transform is to analyze the signal in multi-resolution or multi-scaling, which is very suitable for the logarithmic characteristics of human-eye visual system on the frequency perception.

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Section: A Fractal Image Compression Methods Based On Multi-wavelet (Ymentioning

confidence: 99%

A Fractal Image Compression Method Based on Multi-Wavelet

2015

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“…In video coding, the block-based coding has been widely used in many video compression standards, including MPEG-2 [1], H.263 [2] and H.264 [3]. The disadvantage of the block-based coding is bad subjective effects of reconstructed video sequence at low bit rates [4]. Now in many applications such as video conference, telemedicine and remote monitoring, observers tend to focus on some objects in the video sequence, whereas they are not interested in other objects, which promote the development of the object-based video coding.…”

Section: Introductionmentioning

confidence: 99%

Video Coding Based on Shape-Adaptive All Phase Biorthogonal Transform and MPEG-4

Wang¹,

Wang²,

Zhou³

et al. 2015

jcm

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Abstract-This paper proposes an efficient video coding algorithm based on shape-adaptive all phase biorthogonal transform (SA-APBT) and MPEG-4. Firstly, the input video sequence is segmented into many arbitrarily shaped video objects. Then the motion, shape and texture of all video objects are encoded in accordance with priority. Shape coding uses context-based arithmetic encoding (CAE). SA-APBT and uniform quantization method are adopted in texture coding. Experimental results show that reconstructed video sequence using video coding algorithm based on SA-APBT and MPEG-4 obtains better effects including objective quality and subjective quality compared with the one based on SA-DCT. And the proposed algorithm uses uniform quantization instead of complex quantization table in MPEG-4, which makes hardware implementation easier.Index Terms-Video coding, MPEG-4, shape-adaptive all phase biorthogonal transform (SA-APBT), video object The foreground is respectively encoded according to MPEG-4 video coding algorithm based on SA-APBT and the one based on SA-DCT using the advanced coding

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“…The regions can be defined according to the previously computed segmentation map and are encoded independently of each other. Object based stereo video compression using the combinations of shape-adaptive DCT and fractals is introduced in [21]. Mobile videos are compressed using fractal, [22] in which genetic algorithm and particle swarm optimization techniques are used to improve the quality of video and speed up factor respectively.…”

Section: Related Workmentioning

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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Object-based stereo video compression using fractals and shape-adaptive DCT

Cited by 24 publications

References 18 publications

A Fractal Image Compression Method Based on Multi-Wavelet

A Fractal Image Compression Method Based on Multi-Wavelet

Video Coding Based on Shape-Adaptive All Phase Biorthogonal Transform and MPEG-4

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

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