Image compression consists of two main parts: encoding and decoding. One of the important problems of the fractal theory is the long encoding implementation time, which hindered the acceptance of fractal image compres...Image compression consists of two main parts: encoding and decoding. One of the important problems of the fractal theory is the long encoding implementation time, which hindered the acceptance of fractal image compression as a practical method. The long encoding time results from the need to perform a large number of domain-range matches, the total encoding time is the product of the number of matches and the time to perform each match. In order to improve encoding speed, a hybrid method combining features extraction and self-organization network has been provided, which is based on the feature extraction approach the comparison pixels by pixels between the feature of range blocks and domains blocks. The efficiency of the new method was been proved by examples.展开更多
An irregular segmented region coding algorithm based on pulse coupled neural network(PCNN) is presented. PCNN has the property of pulse-coupled and changeable threshold, through which these adjacent pixels with approx...An irregular segmented region coding algorithm based on pulse coupled neural network(PCNN) is presented. PCNN has the property of pulse-coupled and changeable threshold, through which these adjacent pixels with approximate gray values can be activated simultaneously. One can draw a conclusion that PCNN has the advantage of realizing the regional segmentation, and the details of original image can be achieved by the parameter adjustment of segmented images, and at the same time, the trivial segmented regions can be avoided. For the better approximation of irregular segmented regions, the Gram-Schmidt method, by which a group of orthonormal basis functions is constructed from a group of linear independent initial base functions, is adopted. Because of the orthonormal reconstructing method, the quality of reconstructed image can be greatly improved and the progressive image transmission will also be possible.展开更多
To get the high compression ratio as well as the high-quality reconstructed image, an effective image compression scheme named irregular segmentation region coding based on spiking cortical model（ISRCS） is presented...To get the high compression ratio as well as the high-quality reconstructed image, an effective image compression scheme named irregular segmentation region coding based on spiking cortical model（ISRCS） is presented. This scheme is region-based and mainly focuses on two issues. Firstly, an appropriate segmentation algorithm is developed to partition an image into some irregular regions and tidy contours, where the crucial regions corresponding to objects are retained and a lot of tiny parts are eliminated. The irregular regions and contours are coded using different methods respectively in the next step. The other issue is the coding method of contours where an efficient and novel chain code is employed. This scheme tries to find a compromise between the quality of reconstructed images and the compression ratio. Some principles and experiments are conducted and the results show its higher performance compared with other compression technologies, in terms of higher quality of reconstructed images, higher compression ratio and less time consuming.展开更多
The method of color quantization and the technique of color spatial quantization based onKohonen neural network are presented in this paper.The later is actually a method of matrixquantization.Using Kohonen NN a palet...The method of color quantization and the technique of color spatial quantization based onKohonen neural network are presented in this paper.The later is actually a method of matrixquantization.Using Kohonen NN a palette and a codebook for color spatial quantization canbe easily obtained.Image compression techniques for digital areonautical maps must be cho-sen to allow rapid decompression and display while maximizing the compression ratio and im-age quality.The palette-based compression technique uses a palette and a codebook based onpalette for color spatial quantization as double look-up -tables,making image decompressionand display just a quick and simple process of looking up the two tables.展开更多
土壤养分具有变异性,其变异性特征能够反映区域生态功能和景观格局的动态变化,是土壤的重要属性之一。本文从土壤养分空间变异的研究意义出发,通过对相关文献的阅读分析,简述了国内外关于土壤养分空间变异研究的发展历程和研究现状,分...土壤养分具有变异性,其变异性特征能够反映区域生态功能和景观格局的动态变化,是土壤的重要属性之一。本文从土壤养分空间变异的研究意义出发,通过对相关文献的阅读分析,简述了国内外关于土壤养分空间变异研究的发展历程和研究现状,分析了土壤养分空间变异的来源,简述了地统计学、地理信息系统(Geographic Information System, GIS)、遥感以及人工神经网络等研究方法在土壤养分空间变异研究的应用现状,并对目前研究所存在的问题进行了剖析,在此基础上对未来的研究方向进行了展望。展开更多
This paper presents a scheme for improving encoding time for fractal image compression. The approachcombines feature extraction with domain classification using a selforganizing neural network. Feature extractionreduc...This paper presents a scheme for improving encoding time for fractal image compression. The approachcombines feature extraction with domain classification using a selforganizing neural network. Feature extractionreduces the dimensionalics of the problem and enables the neural network to be trained on an image separate fromthe test image. The seaorganizing network introduces a neighborhood topology for classytcation, and alsoeliminates the need to specify a prior set of appropriate image classes. The network organizes itself according to thedistribution of the image features observed during the training. The paper presents results showing that thisclassification approach can reduce encoding time by two orders of magnitude while maintaining comparableaccuracy and compression performance.展开更多
文摘Image compression consists of two main parts: encoding and decoding. One of the important problems of the fractal theory is the long encoding implementation time, which hindered the acceptance of fractal image compression as a practical method. The long encoding time results from the need to perform a large number of domain-range matches, the total encoding time is the product of the number of matches and the time to perform each match. In order to improve encoding speed, a hybrid method combining features extraction and self-organization network has been provided, which is based on the feature extraction approach the comparison pixels by pixels between the feature of range blocks and domains blocks. The efficiency of the new method was been proved by examples.
基金National Natural Science Foundation of China(60572011) 985 Special Study Project(LZ85 -231 -582627)
文摘An irregular segmented region coding algorithm based on pulse coupled neural network(PCNN) is presented. PCNN has the property of pulse-coupled and changeable threshold, through which these adjacent pixels with approximate gray values can be activated simultaneously. One can draw a conclusion that PCNN has the advantage of realizing the regional segmentation, and the details of original image can be achieved by the parameter adjustment of segmented images, and at the same time, the trivial segmented regions can be avoided. For the better approximation of irregular segmented regions, the Gram-Schmidt method, by which a group of orthonormal basis functions is constructed from a group of linear independent initial base functions, is adopted. Because of the orthonormal reconstructing method, the quality of reconstructed image can be greatly improved and the progressive image transmission will also be possible.
基金supported by the National Science Foundation of China(60872109)the Program for New Century Excellent Talents in University(NCET-06-0900)
文摘To get the high compression ratio as well as the high-quality reconstructed image, an effective image compression scheme named irregular segmentation region coding based on spiking cortical model（ISRCS） is presented. This scheme is region-based and mainly focuses on two issues. Firstly, an appropriate segmentation algorithm is developed to partition an image into some irregular regions and tidy contours, where the crucial regions corresponding to objects are retained and a lot of tiny parts are eliminated. The irregular regions and contours are coded using different methods respectively in the next step. The other issue is the coding method of contours where an efficient and novel chain code is employed. This scheme tries to find a compromise between the quality of reconstructed images and the compression ratio. Some principles and experiments are conducted and the results show its higher performance compared with other compression technologies, in terms of higher quality of reconstructed images, higher compression ratio and less time consuming.
文摘The method of color quantization and the technique of color spatial quantization based onKohonen neural network are presented in this paper.The later is actually a method of matrixquantization.Using Kohonen NN a palette and a codebook for color spatial quantization canbe easily obtained.Image compression techniques for digital areonautical maps must be cho-sen to allow rapid decompression and display while maximizing the compression ratio and im-age quality.The palette-based compression technique uses a palette and a codebook based onpalette for color spatial quantization as double look-up -tables,making image decompressionand display just a quick and simple process of looking up the two tables.
文摘土壤养分具有变异性,其变异性特征能够反映区域生态功能和景观格局的动态变化,是土壤的重要属性之一。本文从土壤养分空间变异的研究意义出发,通过对相关文献的阅读分析,简述了国内外关于土壤养分空间变异研究的发展历程和研究现状,分析了土壤养分空间变异的来源,简述了地统计学、地理信息系统(Geographic Information System, GIS)、遥感以及人工神经网络等研究方法在土壤养分空间变异研究的应用现状,并对目前研究所存在的问题进行了剖析,在此基础上对未来的研究方向进行了展望。
文摘This paper presents a scheme for improving encoding time for fractal image compression. The approachcombines feature extraction with domain classification using a selforganizing neural network. Feature extractionreduces the dimensionalics of the problem and enables the neural network to be trained on an image separate fromthe test image. The seaorganizing network introduces a neighborhood topology for classytcation, and alsoeliminates the need to specify a prior set of appropriate image classes. The network organizes itself according to thedistribution of the image features observed during the training. The paper presents results showing that thisclassification approach can reduce encoding time by two orders of magnitude while maintaining comparableaccuracy and compression performance.
