Computer analysis of images and patterns : proceedings of the ... International Conference on Automatic Image Processing. International Conference on Automatic Image Processing最新文献
Pub Date : 1997-10-26DOI: 10.1109/ICIP.1997.638807
Pierre Kornprobst, R. Deriche, G. Aubert
We present a new approach based on partial differential equations (PDE) to restore noisy blurred images. After studying the methods to denoise images, staying as close as possible to the input image and methods to restore discontinuities, we propose a new scheme which combines all this schemes. A quantified numerical test on a synthetic image demonstrates the efficiency of our scheme and the role of varying the parameters for denoising, enhancement and coupling. A result on a real image is also presented.
{"title":"Image coupling, restoration and enhancement via PDE's","authors":"Pierre Kornprobst, R. Deriche, G. Aubert","doi":"10.1109/ICIP.1997.638807","DOIUrl":"https://doi.org/10.1109/ICIP.1997.638807","url":null,"abstract":"We present a new approach based on partial differential equations (PDE) to restore noisy blurred images. After studying the methods to denoise images, staying as close as possible to the input image and methods to restore discontinuities, we propose a new scheme which combines all this schemes. A quantified numerical test on a synthetic image demonstrates the efficiency of our scheme and the role of varying the parameters for denoising, enhancement and coupling. A result on a real image is also presented.","PeriodicalId":92344,"journal":{"name":"Computer analysis of images and patterns : proceedings of the ... International Conference on Automatic Image Processing. International Conference on Automatic Image Processing","volume":"103 1","pages":"458-461 vol.2"},"PeriodicalIF":0.0,"publicationDate":"1997-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86530927","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1997-10-26DOI: 10.1109/ICIP.1997.632207
J. Andrew
In this paper we propose a simple image compression method that efficiently codes transform images. This work has been stimulated by the EZW and SPIHT image compression methods. However, the compression method we describe is not embedded in the sense employed previously, nor does it utilise the concept of a zerotree or related structure. The only characteristic of transform imagery utilised is that of energy clustering in frequency and in space. Two variants of the coding method are considered for image compression. One gives a hierarchical image code when employed with a discrete wavelet transform, while the other is suitable for block based coding.
{"title":"A simple and efficient hierarchical image coder","authors":"J. Andrew","doi":"10.1109/ICIP.1997.632207","DOIUrl":"https://doi.org/10.1109/ICIP.1997.632207","url":null,"abstract":"In this paper we propose a simple image compression method that efficiently codes transform images. This work has been stimulated by the EZW and SPIHT image compression methods. However, the compression method we describe is not embedded in the sense employed previously, nor does it utilise the concept of a zerotree or related structure. The only characteristic of transform imagery utilised is that of energy clustering in frequency and in space. Two variants of the coding method are considered for image compression. One gives a hierarchical image code when employed with a discrete wavelet transform, while the other is suitable for block based coding.","PeriodicalId":92344,"journal":{"name":"Computer analysis of images and patterns : proceedings of the ... International Conference on Automatic Image Processing. International Conference on Automatic Image Processing","volume":"35 1","pages":"658-661 vol.3"},"PeriodicalIF":0.0,"publicationDate":"1997-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82655653","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1997-10-26DOI: 10.1109/ICIP.1997.632177
Huai Li, K. J. Liu, S. Lo, Y. Wang
We have developed a combined method utilizing morphological operations, a finite generalized Gaussian mixture (FGGM) modeling, and a contextual Bayesian relaxation labeling technique (CBRL) to enhance and extract suspicious masses. A feature space is constructed based on multiple feature extraction from the regions of interest (ROIs). Finally, a multi-modular probabilistic decision-based classifier is employed to distinguish true masses from non-masses.
{"title":"Stochastic model and probabilistic decision-based classifier for mass detection in digital mammography","authors":"Huai Li, K. J. Liu, S. Lo, Y. Wang","doi":"10.1109/ICIP.1997.632177","DOIUrl":"https://doi.org/10.1109/ICIP.1997.632177","url":null,"abstract":"We have developed a combined method utilizing morphological operations, a finite generalized Gaussian mixture (FGGM) modeling, and a contextual Bayesian relaxation labeling technique (CBRL) to enhance and extract suspicious masses. A feature space is constructed based on multiple feature extraction from the regions of interest (ROIs). Finally, a multi-modular probabilistic decision-based classifier is employed to distinguish true masses from non-masses.","PeriodicalId":92344,"journal":{"name":"Computer analysis of images and patterns : proceedings of the ... International Conference on Automatic Image Processing. International Conference on Automatic Image Processing","volume":"40 1","pages":"539-542 vol.3"},"PeriodicalIF":0.0,"publicationDate":"1997-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88909464","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1997-10-26DOI: 10.1109/ICIP.1997.638756
David M. Bethel, D. Monro
We consider the rate/distortion benefits of aspects of fractal image compression, and introduce a new method of pruning the pool of parent blocks for optimum performance. Previous work questioned the value of searching in fractal compression, and found that the code used to represent block offsets was not compensated for by decreased error. This was because the searching process predominantly chose local parent blocks. Here we revisit this question using improved basis functions and orthogonalized parent blocks. The basis function is a limited number of DCT coefficients which has very low complexity compared to wavelet transforms or full DCTs. A zero-searching fractal transform in which the parent block is centred over the child block improves the basis function approximation. With orthogonalized parent blocks, searching of the image gives a slight PSNR benefit at higher compression ratios. A new scheme, in which the pool of parent blocks is pruned according to a rate/distortion criterion, gives greater improvement, and guarantees optimal use of the parent pool. The method advances the technique of fractal image compression and shows how to use fractal terms to improve the rate/distortion performance of image coding by any basis approximation.
{"title":"Optimum parent pruning in fractal compression","authors":"David M. Bethel, D. Monro","doi":"10.1109/ICIP.1997.638756","DOIUrl":"https://doi.org/10.1109/ICIP.1997.638756","url":null,"abstract":"We consider the rate/distortion benefits of aspects of fractal image compression, and introduce a new method of pruning the pool of parent blocks for optimum performance. Previous work questioned the value of searching in fractal compression, and found that the code used to represent block offsets was not compensated for by decreased error. This was because the searching process predominantly chose local parent blocks. Here we revisit this question using improved basis functions and orthogonalized parent blocks. The basis function is a limited number of DCT coefficients which has very low complexity compared to wavelet transforms or full DCTs. A zero-searching fractal transform in which the parent block is centred over the child block improves the basis function approximation. With orthogonalized parent blocks, searching of the image gives a slight PSNR benefit at higher compression ratios. A new scheme, in which the pool of parent blocks is pruned according to a rate/distortion criterion, gives greater improvement, and guarantees optimal use of the parent pool. The method advances the technique of fractal image compression and shows how to use fractal terms to improve the rate/distortion performance of image coding by any basis approximation.","PeriodicalId":92344,"journal":{"name":"Computer analysis of images and patterns : proceedings of the ... International Conference on Automatic Image Processing. International Conference on Automatic Image Processing","volume":"38 1","pages":"318-321 vol.2"},"PeriodicalIF":0.0,"publicationDate":"1997-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79214638","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1997-10-26DOI: 10.1109/ICIP.1997.632066
K. Hassanein, S. Wesolkowski
This paper describes a new method for stroke extraction from grayscale images based on an effective local adaptive kernel technique that assigns a mark for each pixel in the image signifying its relative importance with respect to neighboring pixels. The assigned marks are based on accumulating evidence of the relative importance of each pixel based on multiple comparisons with neighboring pixels under different windows. A global threshold is then applied to the marks produced in the first step to reach a conclusion as to whether a pixel ought to be preserved as part of a stroke or be dropped as part of the background. This technique effectively combines local and global thresholding techniques and shows promising performance especially on images with non-uniform backgrounds or embedded light strokes. The advantage of this scheme is also demonstrated in terms of superior overall amount recognition performance for financial document processing systems utilizing it.
{"title":"Stroke extraction from grayscale images of financial documents based on figures of importance","authors":"K. Hassanein, S. Wesolkowski","doi":"10.1109/ICIP.1997.632066","DOIUrl":"https://doi.org/10.1109/ICIP.1997.632066","url":null,"abstract":"This paper describes a new method for stroke extraction from grayscale images based on an effective local adaptive kernel technique that assigns a mark for each pixel in the image signifying its relative importance with respect to neighboring pixels. The assigned marks are based on accumulating evidence of the relative importance of each pixel based on multiple comparisons with neighboring pixels under different windows. A global threshold is then applied to the marks produced in the first step to reach a conclusion as to whether a pixel ought to be preserved as part of a stroke or be dropped as part of the background. This technique effectively combines local and global thresholding techniques and shows promising performance especially on images with non-uniform backgrounds or embedded light strokes. The advantage of this scheme is also demonstrated in terms of superior overall amount recognition performance for financial document processing systems utilizing it.","PeriodicalId":92344,"journal":{"name":"Computer analysis of images and patterns : proceedings of the ... International Conference on Automatic Image Processing. International Conference on Automatic Image Processing","volume":"89 1","pages":"224-227 vol.3"},"PeriodicalIF":0.0,"publicationDate":"1997-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83209288","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1997-10-26DOI: 10.1109/ICIP.1997.638752
Hiroyuki Honda, M. Haseyama, H. Kitajima, S. Matsumoto
Fractal image compression using the iterative function system (IFS) is based on the collage theorem proposed by Barnsley et al. (1986). In this conventional method, the errors between the reconstructed image and original image may be greater than the errors between the collage and original image because the collage theorem does not guarantee the former errors to be smaller than the latter errors. This paper proposes an extended collage theorem. An IFS algorithm based on this theorem determines the parameters after iterations of the contraction mappings. An image reconstructed according to the new theorem has higher quality than one based on the existing collage theorem. The reconstructed image can be gotten by fewer iterations than by the conventional IFS.
利用迭代函数系统(IFS)进行分形图像压缩是基于Barnsley et al.(1986)提出的拼贴定理。在这种常规方法中，由于拼贴定理不能保证前者的误差小于后者的误差，因此重构图像与原始图像之间的误差可能大于拼贴图像与原始图像之间的误差。本文提出了一个扩展的拼贴定理。基于该定理的IFS算法在收缩映射迭代后确定参数。根据新定理重建的图像比基于现有拼贴定理重建的图像质量更高。与传统的IFS相比，重构图像的迭代次数更少。
{"title":"Extension of the collage theorem","authors":"Hiroyuki Honda, M. Haseyama, H. Kitajima, S. Matsumoto","doi":"10.1109/ICIP.1997.638752","DOIUrl":"https://doi.org/10.1109/ICIP.1997.638752","url":null,"abstract":"Fractal image compression using the iterative function system (IFS) is based on the collage theorem proposed by Barnsley et al. (1986). In this conventional method, the errors between the reconstructed image and original image may be greater than the errors between the collage and original image because the collage theorem does not guarantee the former errors to be smaller than the latter errors. This paper proposes an extended collage theorem. An IFS algorithm based on this theorem determines the parameters after iterations of the contraction mappings. An image reconstructed according to the new theorem has higher quality than one based on the existing collage theorem. The reconstructed image can be gotten by fewer iterations than by the conventional IFS.","PeriodicalId":92344,"journal":{"name":"Computer analysis of images and patterns : proceedings of the ... International Conference on Automatic Image Processing. International Conference on Automatic Image Processing","volume":"51 1","pages":"306-309 vol.2"},"PeriodicalIF":0.0,"publicationDate":"1997-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83285760","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1997-10-26DOI: 10.1109/ICIP.1997.638763
R. Queiroz
We present techniques that allow the processing of an image in the "JPEG-compressed" domain. The goal is to reduce memory requirements while increasing the speed by avoiding decompression and space domain operations. An effort is made to implement the minimum number of JPEG basic operations. Techniques are presented for scaling, previewing, rotating, mirroring, cropping, recompressing, and segmenting JPEG-compressed data.
{"title":"Processing JPEG-compressed images","authors":"R. Queiroz","doi":"10.1109/ICIP.1997.638763","DOIUrl":"https://doi.org/10.1109/ICIP.1997.638763","url":null,"abstract":"We present techniques that allow the processing of an image in the \"JPEG-compressed\" domain. The goal is to reduce memory requirements while increasing the speed by avoiding decompression and space domain operations. An effort is made to implement the minimum number of JPEG basic operations. Techniques are presented for scaling, previewing, rotating, mirroring, cropping, recompressing, and segmenting JPEG-compressed data.","PeriodicalId":92344,"journal":{"name":"Computer analysis of images and patterns : proceedings of the ... International Conference on Automatic Image Processing. International Conference on Automatic Image Processing","volume":"21 1","pages":"334-337 vol.2"},"PeriodicalIF":0.0,"publicationDate":"1997-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83334102","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1997-10-26DOI: 10.1109/ICIP.1997.647997
H. Wang, C.-C. Jay Kuo
An embedded wavelet coder algorithm which adopts different threshold values in different subbands is proposed in this work. The new image coder, called the multi-threshold wavelet coder (MTWC), achieves a better rate-distortion performance than existing embedded wavelet coders for applications requiring higher quality with higher bit rates (e.g. greater than 1 bpp). Another advantage of MTWC is its lower computational complexity. The superior performance of MWC can be explained by examining the evolution of the distortion distribution in each subband as image data are compressed in the embedded coding process. Experimental results are given to demonstrate the performance of MTWC at various bit rates.
{"title":"A multi-threshold wavelet coder (MTWC) for high fidelity image compression","authors":"H. Wang, C.-C. Jay Kuo","doi":"10.1109/ICIP.1997.647997","DOIUrl":"https://doi.org/10.1109/ICIP.1997.647997","url":null,"abstract":"An embedded wavelet coder algorithm which adopts different threshold values in different subbands is proposed in this work. The new image coder, called the multi-threshold wavelet coder (MTWC), achieves a better rate-distortion performance than existing embedded wavelet coders for applications requiring higher quality with higher bit rates (e.g. greater than 1 bpp). Another advantage of MTWC is its lower computational complexity. The superior performance of MWC can be explained by examining the evolution of the distortion distribution in each subband as image data are compressed in the embedded coding process. Experimental results are given to demonstrate the performance of MTWC at various bit rates.","PeriodicalId":92344,"journal":{"name":"Computer analysis of images and patterns : proceedings of the ... International Conference on Automatic Image Processing. International Conference on Automatic Image Processing","volume":"16 1","pages":"652-655 vol.1"},"PeriodicalIF":0.0,"publicationDate":"1997-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81171411","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1997-10-26DOI: 10.1109/ICIP.1997.648087
P. Scheunders, S. D. Backer
A competitive learning scheme for color image quantization is elaborated, in which the dithering process for eliminating contouring effects, instead of performed a posteriori, is imbedded in the quantization process. Quantization is performed by clustering in color space. The dithering process is a simple error diffusion which diffuses the quantization error made by one pixel to its local neighborhood. For small color palettes, this is demonstrated to improve the visual quality of quantized images.
{"title":"Joint quantization and error diffusion of color images using competitive learning","authors":"P. Scheunders, S. D. Backer","doi":"10.1109/ICIP.1997.648087","DOIUrl":"https://doi.org/10.1109/ICIP.1997.648087","url":null,"abstract":"A competitive learning scheme for color image quantization is elaborated, in which the dithering process for eliminating contouring effects, instead of performed a posteriori, is imbedded in the quantization process. Quantization is performed by clustering in color space. The dithering process is a simple error diffusion which diffuses the quantization error made by one pixel to its local neighborhood. For small color palettes, this is demonstrated to improve the visual quality of quantized images.","PeriodicalId":92344,"journal":{"name":"Computer analysis of images and patterns : proceedings of the ... International Conference on Automatic Image Processing. International Conference on Automatic Image Processing","volume":"24 1","pages":"811-814 vol.1"},"PeriodicalIF":0.0,"publicationDate":"1997-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83499332","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1997-10-26DOI: 10.1109/ICIP.1997.638741
Ho-Youl Jung, R. Prost
In this paper, a new approach is proposed, the rounding transform (RT) based lossless subband coding. For the such purpose, an extended version of RT, namely overlapping RT (ORT), is defined in the Z-transform domain and used to develop the lossless subband coding system. The main idea is that the polyphase matrix of the analysis filter bank is decomposed into several ORT matrices of size 2 by 2. Compared to the previous scheme (the lifting), the proposed scheme gives not only simpler mathematical representation, but also allows various possibilities when a given filter bank is implemented. As examples, five filter banks are applied to lossless image compression by the proposed ORT and their performances are compared in terms of the total lossless first order entropy.
{"title":"Rounding transform based approach for lossless subband coding","authors":"Ho-Youl Jung, R. Prost","doi":"10.1109/ICIP.1997.638741","DOIUrl":"https://doi.org/10.1109/ICIP.1997.638741","url":null,"abstract":"In this paper, a new approach is proposed, the rounding transform (RT) based lossless subband coding. For the such purpose, an extended version of RT, namely overlapping RT (ORT), is defined in the Z-transform domain and used to develop the lossless subband coding system. The main idea is that the polyphase matrix of the analysis filter bank is decomposed into several ORT matrices of size 2 by 2. Compared to the previous scheme (the lifting), the proposed scheme gives not only simpler mathematical representation, but also allows various possibilities when a given filter bank is implemented. As examples, five filter banks are applied to lossless image compression by the proposed ORT and their performances are compared in terms of the total lossless first order entropy.","PeriodicalId":92344,"journal":{"name":"Computer analysis of images and patterns : proceedings of the ... International Conference on Automatic Image Processing. International Conference on Automatic Image Processing","volume":"10 1","pages":"274-277 vol.2"},"PeriodicalIF":0.0,"publicationDate":"1997-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87229627","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Computer analysis of images and patterns : proceedings of the ... International Conference on Automatic Image Processing. International Conference on Automatic Image Processing
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