This paper utilizes a spatial texture correlation and the intelligent classification algorithm （ICA） search strategy to speed up the encoding process and improve the bit rate for fractal image compression. Texture f...This paper utilizes a spatial texture correlation and the intelligent classification algorithm （ICA） search strategy to speed up the encoding process and improve the bit rate for fractal image compression. Texture features is one of the most important properties for the representation of an image. Entropy and maximum entry from co-occurrence matrices are used for representing texture features in an image. For a range block, concerned domain blocks of neighbouring range blocks with similar texture features can be searched. In addition, domain blocks with similar texture features are searched in the ICA search process. Experiments show that in comparison with some typical methods, the proposed algorithm significantly speeds up the encoding process and achieves a higher compression ratio, with a slight diminution in the quality of the reconstructed image; in comparison with a spatial correlation scheme, the proposed scheme spends much less encoding time while the compression ratio and the quality of the reconstructed image are almost the same.展开更多
A chaos-based cryptosystem for fractal image coding is proposed. The Renyi chaotic map is employed to determine the order of processing the range blocks and to generate the keystream for masking the encoded sequence. ...A chaos-based cryptosystem for fractal image coding is proposed. The Renyi chaotic map is employed to determine the order of processing the range blocks and to generate the keystream for masking the encoded sequence. Compared with the standard approach of fraetal image coding followed by the Advanced Encryption Standard, our scheme offers a higher sensitivity to both plaintext and ciphertext at a comparable operating efficiency. The keystream generated by the Renyi chaotic map passes the randomness tests set by the United States National Institute of Standards and Technology, and so the proposed scheme is sensitive to the key.展开更多
Based on Jacquin's work. this paper presents an adaptive block-based fractal image coding scheme. Firstly. masking functions are used to classify range blocks and weight the mean Square error (MSE) of images. Seco...Based on Jacquin's work. this paper presents an adaptive block-based fractal image coding scheme. Firstly. masking functions are used to classify range blocks and weight the mean Square error (MSE) of images. Secondly, an adaptive block partition scheme is introduced by developing the quadtree partition method. Thirdly. a piecewise uniform quantization strategy is appled to quantize the luminance shifting. Finally. experiment results are shown and compared with what reported by Jacquin and Lu to verify the validity of the methods addressed by the authors.展开更多
To achieve high-quality image compression of a floral canopy,a region of interest(ROI)mask of the wavelet domain was generated through the automatic identification of the canopy ROI and lifting the bit-plane of the RO...To achieve high-quality image compression of a floral canopy,a region of interest(ROI)mask of the wavelet domain was generated through the automatic identification of the canopy ROI and lifting the bit-plane of the ROI to obtain priority of coding for the ROI-set partitioning in hierarchical trees(ROI-SPIHT)coding.The embedded zerotree wavelet(EZW)coding was conducted for the background(BG)region of the image and a relatively more low-frequency wavelet coefficient was obtained using a relatively small amount of coding.Through the weighing factor r of the ROI coding amount,the proportion of the ROI and BG coding amount was dynamically adjusted to generate embedded,truncatable bit streams.Despite the location of truncation,the image information and ROI mask information required by the decoder can be guaranteed to achieve high-quality compression and reconstruction of the image ROI.The results indicated that under the same bit rate,the larger the r value is,the larger the peak-signal-to-noise ratio(PSNR)for the ROI reconstructed image and the smaller the PSNR for the BG reconstructed image.In the range of 0.07-1.09 bpp,the PSNR of the ROI reconstructed image was 42.65%higher on average than that of the BG reconstructed image,43.95%higher on average than that of the composite image of the ROI and BG(ALL),and 16.84%higher on average than that of the standard SPIHT reconstructed image.Additionally,the mean square error of the quality evaluation index and similarity for the ROI reconstructed image were both better than those for the BG,ALL,and standard SPIHT reconstructed images.The texture distortion of the ALL image was smaller than that of the SPIHT reconstructed image,indicating that the image compression algorithm based on the mask hybrid coding for ROI(ROI-MHC)is capable of improving the reconstruction quality of an ROI image.When the weighing factor r is a fixed value,as the proportion of ROI(a)increases,the quality of ROI image reconstruction gradually decreases.Therefore,upon the application of the ROI-MHC image compression algorithm,high-quality reconstruction of the ROI image can be achieved through dynamically configuring r according to a.Under the same bit rate,the quality of the ROI-MHC image compression is higher than that of current compression algorithms of same classes and offers promising application opportunities.展开更多
In this paper, the 3-D Wavelet-Fractal coder was used to compress the hyperspectral remote sensing image, which is a combination of 3-D improved set partitioning in hierarchical trees （SPIHT） coding and 3-D fractal ...In this paper, the 3-D Wavelet-Fractal coder was used to compress the hyperspectral remote sensing image, which is a combination of 3-D improved set partitioning in hierarchical trees （SPIHT） coding and 3-D fractal coding. Hyperspectral image date cube was first translated by 3-D wavelet and the 3-D fractal compression ceding was applied to lowest frequency subband. The remaining coefficients of higher frequency sub-bands were encoding by 3-D improved SPIHT. We used the block set instead of the hierarchical trees to enhance SPIHT＇s flexibility. The classical eight kinds of affme transformations in 2-D fractal image compression were generalized to nineteen for the 3-D fractal image compression. The new compression method had been tested on MATLAB. The experiment results indicate that we can gain high compression ratios and the information loss is acceptable.展开更多
Starting with a fractal-based image-compression algorithm based on wavelet transformation for hyperspectral images, the authors were able to obtain more spectral bands with the help of of hyperspectral remote sensing....Starting with a fractal-based image-compression algorithm based on wavelet transformation for hyperspectral images, the authors were able to obtain more spectral bands with the help of of hyperspectral remote sensing. Because large amounts of data and limited bandwidth complicate the storage and transmission of data measured by TB-level bits, it is important to compress image data acquired by hyperspectral sensors such as MODIS, PHI, and OMIS; otherwise, conventional lossless compression algorithms cannot reach adequate compression ratios. Other loss-compression methods can reach high compression ratios but lack good image fidelity, especially for hyperspectral image data. Among the third generation of image compression algorithms, fractal image compression based on wavelet transformation is superior to traditional compression methods,because it has high compression ratios and good image fidelity, and requires less computing time. To keep the spectral dimension invariable, the authors compared the results of two compression algorithms based on the storage-file structures of BSQ and of BIP, and improved the HV and Quadtree partitioning and domain-range matching algorithms in order to accelerate their encode/decode efficiency. The authors' Hyperspectral Image Process and Analysis System (HIPAS) software used a VC++6.0 integrated development environment (IDE), with which good experimental results were obtained. Possible modifications of the algorithm and limitations of the method are also discussed.展开更多
Fractal image compression is a completely new method to compress images by searching and exploiting the self similarity of the whole image . Fractal Block Coding (FBC) is a practicable fractal coding schem...Fractal image compression is a completely new method to compress images by searching and exploiting the self similarity of the whole image . Fractal Block Coding (FBC) is a practicable fractal coding scheme with annoying slow encoding speed . In this paper, we classify the image blocks by Classified Vector Quantization (CVQ) technique and present an Adaptive Block Truncation Coding (ABTC) scheme to process the midrange blocks in the image. By this method , we reduce the encoding time to one forty fifth comparing to ordinary FBC method with little change in compression ratio and a little decreased coded image quality.展开更多
Currently,in multimedia and image processing technologies, implementing special kinds of image manipulation operations by dealing directly with the compressed image is a work worthy to be concerned with. Theoretical a...Currently,in multimedia and image processing technologies, implementing special kinds of image manipulation operations by dealing directly with the compressed image is a work worthy to be concerned with. Theoretical analysis and experiment haVe indicated that some kinds of image processing works can be done very well by dealing with compressed image. In Ans paper, we give some efficient image manipulation operation algorithms operating on the compressed image data. These algorithms have advantages in computing complexity, storage space retirement and image quality.展开更多
基金supported by the National Natural Science Foundation of China (Grant Nos. 60573172 and 60973152)the Superior University Doctor Subject Special Scientific Research Foundation of China (Grant No. 20070141014)the Natural Science Foundation of Liaoning Province of China (Grant No. 20082165)
文摘This paper utilizes a spatial texture correlation and the intelligent classification algorithm （ICA） search strategy to speed up the encoding process and improve the bit rate for fractal image compression. Texture features is one of the most important properties for the representation of an image. Entropy and maximum entry from co-occurrence matrices are used for representing texture features in an image. For a range block, concerned domain blocks of neighbouring range blocks with similar texture features can be searched. In addition, domain blocks with similar texture features are searched in the ICA search process. Experiments show that in comparison with some typical methods, the proposed algorithm significantly speeds up the encoding process and achieves a higher compression ratio, with a slight diminution in the quality of the reconstructed image; in comparison with a spatial correlation scheme, the proposed scheme spends much less encoding time while the compression ratio and the quality of the reconstructed image are almost the same.
基金Project supported by the Research Grants Council of the Hong Kong Special Administrative Region,China(Grant No.CityU123009)
文摘A chaos-based cryptosystem for fractal image coding is proposed. The Renyi chaotic map is employed to determine the order of processing the range blocks and to generate the keystream for masking the encoded sequence. Compared with the standard approach of fraetal image coding followed by the Advanced Encryption Standard, our scheme offers a higher sensitivity to both plaintext and ciphertext at a comparable operating efficiency. The keystream generated by the Renyi chaotic map passes the randomness tests set by the United States National Institute of Standards and Technology, and so the proposed scheme is sensitive to the key.
文摘Based on Jacquin's work. this paper presents an adaptive block-based fractal image coding scheme. Firstly. masking functions are used to classify range blocks and weight the mean Square error (MSE) of images. Secondly, an adaptive block partition scheme is introduced by developing the quadtree partition method. Thirdly. a piecewise uniform quantization strategy is appled to quantize the luminance shifting. Finally. experiment results are shown and compared with what reported by Jacquin and Lu to verify the validity of the methods addressed by the authors.
基金support provided by the Natural Science Fundation of Jiangsu Province:Youth Fund(Grant No.BK20170727)the Fundamental Research Funds for the Central Universities(Grant No.KYGX201703)the Natural Science Fundation of Jiangsu Province:Youth Fund(Grant No.BK20150686).
文摘To achieve high-quality image compression of a floral canopy,a region of interest(ROI)mask of the wavelet domain was generated through the automatic identification of the canopy ROI and lifting the bit-plane of the ROI to obtain priority of coding for the ROI-set partitioning in hierarchical trees(ROI-SPIHT)coding.The embedded zerotree wavelet(EZW)coding was conducted for the background(BG)region of the image and a relatively more low-frequency wavelet coefficient was obtained using a relatively small amount of coding.Through the weighing factor r of the ROI coding amount,the proportion of the ROI and BG coding amount was dynamically adjusted to generate embedded,truncatable bit streams.Despite the location of truncation,the image information and ROI mask information required by the decoder can be guaranteed to achieve high-quality compression and reconstruction of the image ROI.The results indicated that under the same bit rate,the larger the r value is,the larger the peak-signal-to-noise ratio(PSNR)for the ROI reconstructed image and the smaller the PSNR for the BG reconstructed image.In the range of 0.07-1.09 bpp,the PSNR of the ROI reconstructed image was 42.65%higher on average than that of the BG reconstructed image,43.95%higher on average than that of the composite image of the ROI and BG(ALL),and 16.84%higher on average than that of the standard SPIHT reconstructed image.Additionally,the mean square error of the quality evaluation index and similarity for the ROI reconstructed image were both better than those for the BG,ALL,and standard SPIHT reconstructed images.The texture distortion of the ALL image was smaller than that of the SPIHT reconstructed image,indicating that the image compression algorithm based on the mask hybrid coding for ROI(ROI-MHC)is capable of improving the reconstruction quality of an ROI image.When the weighing factor r is a fixed value,as the proportion of ROI(a)increases,the quality of ROI image reconstruction gradually decreases.Therefore,upon the application of the ROI-MHC image compression algorithm,high-quality reconstruction of the ROI image can be achieved through dynamically configuring r according to a.Under the same bit rate,the quality of the ROI-MHC image compression is higher than that of current compression algorithms of same classes and offers promising application opportunities.
基金National Natural Science Foundation of China (No.60975084)
文摘In this paper, the 3-D Wavelet-Fractal coder was used to compress the hyperspectral remote sensing image, which is a combination of 3-D improved set partitioning in hierarchical trees （SPIHT） coding and 3-D fractal coding. Hyperspectral image date cube was first translated by 3-D wavelet and the 3-D fractal compression ceding was applied to lowest frequency subband. The remaining coefficients of higher frequency sub-bands were encoding by 3-D improved SPIHT. We used the block set instead of the hierarchical trees to enhance SPIHT＇s flexibility. The classical eight kinds of affme transformations in 2-D fractal image compression were generalized to nineteen for the 3-D fractal image compression. The new compression method had been tested on MATLAB. The experiment results indicate that we can gain high compression ratios and the information loss is acceptable.
文摘Starting with a fractal-based image-compression algorithm based on wavelet transformation for hyperspectral images, the authors were able to obtain more spectral bands with the help of of hyperspectral remote sensing. Because large amounts of data and limited bandwidth complicate the storage and transmission of data measured by TB-level bits, it is important to compress image data acquired by hyperspectral sensors such as MODIS, PHI, and OMIS; otherwise, conventional lossless compression algorithms cannot reach adequate compression ratios. Other loss-compression methods can reach high compression ratios but lack good image fidelity, especially for hyperspectral image data. Among the third generation of image compression algorithms, fractal image compression based on wavelet transformation is superior to traditional compression methods,because it has high compression ratios and good image fidelity, and requires less computing time. To keep the spectral dimension invariable, the authors compared the results of two compression algorithms based on the storage-file structures of BSQ and of BIP, and improved the HV and Quadtree partitioning and domain-range matching algorithms in order to accelerate their encode/decode efficiency. The authors' Hyperspectral Image Process and Analysis System (HIPAS) software used a VC++6.0 integrated development environment (IDE), with which good experimental results were obtained. Possible modifications of the algorithm and limitations of the method are also discussed.
文摘Fractal image compression is a completely new method to compress images by searching and exploiting the self similarity of the whole image . Fractal Block Coding (FBC) is a practicable fractal coding scheme with annoying slow encoding speed . In this paper, we classify the image blocks by Classified Vector Quantization (CVQ) technique and present an Adaptive Block Truncation Coding (ABTC) scheme to process the midrange blocks in the image. By this method , we reduce the encoding time to one forty fifth comparing to ordinary FBC method with little change in compression ratio and a little decreased coded image quality.
文摘Currently,in multimedia and image processing technologies, implementing special kinds of image manipulation operations by dealing directly with the compressed image is a work worthy to be concerned with. Theoretical analysis and experiment haVe indicated that some kinds of image processing works can be done very well by dealing with compressed image. In Ans paper, we give some efficient image manipulation operation algorithms operating on the compressed image data. These algorithms have advantages in computing complexity, storage space retirement and image quality.
