Aiming at content-based image retrieval (CBIR) in fractal domain, this paper puts forward a fast fractal encoding method to extract image features, which is based on a novel non-searching and adaptive quadtree divisio...
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Aiming at content-based image retrieval (CBIR) in fractal domain, this paper puts forward a fast fractal encoding method to extract image features, which is based on a novel non-searching and adaptive quadtree division. As a result, it enhances fractal coding speed sharply, only needs 0.0485 seconds on average for a 256 x 256 image and is approximately 70 times faster than algorithm in addition to good reconstructed image quality. Furthermore, this paper improves image matching algorithm, consequently enhancing the accuracy of query results. In addition, we present a method to further accelerate image retrieval based on the analysis to fractal codes distance and number. Experimental results show that our proposed method is performs highly in retrieval speed and feasible in retrieval accuracy.
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 i...
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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.
Noise removing algorithms of spatial domain and various other domains find much useful in real time noise removal techniques such as medical imaging and satellite imaging applications. The order of noise and performan...
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ISBN:
(纸本)9781467329071;9781467329064
Noise removing algorithms of spatial domain and various other domains find much useful in real time noise removal techniques such as medical imaging and satellite imaging applications. The order of noise and performance measures to be analyzed decides the type of denoising algorithm. The intensity based image denoising procedures and image fractal based denoising procedures are providing wider applications related to the field processing the visual information and structural similarity. In this paper many denoising procedures are analyzed to list out the performance measures of efficient techniques for improving image quality by preserving sharp details.
Both the size and the resolution of images always were key topics in the graphical computing area. Especially, they become more and more relevant in the big data era. We can observe that often a huge amount of data is...
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Both the size and the resolution of images always were key topics in the graphical computing area. Especially, they become more and more relevant in the big data era. We can observe that often a huge amount of data is exchanged by medium/low bandwidth networks or yet, they need to be stored on devices with limited space of memory. In this context, the present paper shows the use of the fractal method for image compression. It is a lossy method known by providing higher indexes of file reduction through a highly time consuming phase. In this way, we developed a model of parallel application for exploiting the power of multiprocessor architectures in order to get the fractal method advantages in a feasible time. The evaluation was done with different-sized images as well as by using two types of machines, one with two and another with four cores. The results demonstrated that both the speedup and efficiency are highly dependent of the number of cores. They emphasized that a large number of threads does not always represent a better performance.
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 i...
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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.
Both the size and the resolution of images always were key topics in the graphical computing ***,they become more and more relevant in the big data *** can observe that often a huge amount of data is exchanged by medi...
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Both the size and the resolution of images always were key topics in the graphical computing ***,they become more and more relevant in the big data *** can observe that often a huge amount of data is exchanged by medium/low bandwidth networks or yet,they need to be stored on devices with limited space of *** this context,the present paper shows the use of the fractal method for image *** is a lossy method known by providing higher indexes of file reduction through a highly time consuming *** this way,we developed a model of parallel application for exploiting the power of multiprocessor architectures in order to get the fractal method advantages in a feasible *** evaluation was done with different-sized images as well as by using two types of machines,one with two and another with four *** results demonstrated that both the speedup and efficiency are highly dependent of the number of *** emphasized that a large number of threads does not always represent a better performance.
Image compression is a technology using as little as possible bits to represent the original image. As wavelet transform has local characteristics on the time and frequency domain, it makes up the deficiency of DCT. M...
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ISBN:
(纸本)9783037853122
Image compression is a technology using as little as possible bits to represent the original image. As wavelet transform has local characteristics on the time and frequency domain, it makes up the deficiency of DCT. Moreover, its multi-resolution characteristics can easily associate with the human visual system (HVS). Besides, wavelet-based image compression is prone to combine with new image coding methods. It has become the research hotspots at present. This paper introduces wavelets theory and discusses the research status and progress of wavelet-based image compression then points out the main problems. Finally, the prospect in the future was presented.
This study presents two watermarking approaches in fractal coding images. The fast method, namely Mean-Classified fractal coding (MCFC), partitions the domain blocks of an image into groups according the mean values. ...
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ISBN:
(纸本)9780769532783
This study presents two watermarking approaches in fractal coding images. The fast method, namely Mean-Classified fractal coding (MCFC), partitions the domain blocks of an image into groups according the mean values. As documented in experimental results, a high embedding capacity can be achieved with good image quality. Moreover, the MCFC is proved of highly robust to against many types of attacks, including JPEG, tampering, and rotating. The second method, namely Hierarchical Block Matching fractal coding (HBMFC), utilizes different domain block sizes to enlarge the searching pool with slightly sacrificing the coding gain. The HBMFC is mainly adapted to fragile watermarking, which can be applied to authentication application to prevent from illegal alteration.
Based on fractal coding and fractal singular value neighbor distance, an improved approach for cell image recognition is proposed in this paper. fractal singular value neighbor distance is brought forward based on fra...
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ISBN:
(纸本)9781424435296
Based on fractal coding and fractal singular value neighbor distance, an improved approach for cell image recognition is proposed in this paper. fractal singular value neighbor distance is brought forward based on fractal neighbor distance and singular value decomposition. fractal coding and local singular value decomposition are used to improve the recognition rate. The experimental results show that the method can keep a good robustness to the variation of illumination, pose and expression, compared with traditional fractal neighbor distances. Furthermore, the method shows that the training time is short and recognition rate is high.
Based on fractal coding and fractal singular value neighbor distance,an improved approach for cell image recognition is proposed in this *** singular value neighbor distance is brought forward based on fractal neighbo...
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Based on fractal coding and fractal singular value neighbor distance,an improved approach for cell image recognition is proposed in this *** singular value neighbor distance is brought forward based on fractal neighbor distance and singular value *** coding and local singular value decomposition are used to improve the recognition *** experimental results show that the method can keep a good robustness to the variation of illumination,pose and expression,compared with traditional fractal neighbor ***,the method shows that the training time is short and recognition rate is high.
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