A novel wavelet-based algorithm for image enhancement is proposed in the paper. On the basis of multiscale analysis, the proposed algorithm solves efficiently the problem of noise over-enhancement, which commonly occu...A novel wavelet-based algorithm for image enhancement is proposed in the paper. On the basis of multiscale analysis, the proposed algorithm solves efficiently the problem of noise over-enhancement, which commonly occurs in the traditional methods for contrast enhancement. The decomposed coefficients at same scales are processed by a nonlinear method, and the coefficients at different scales are enhanced in different degree. During the procedure, the method takes full advantage of the properties of Human visual system so as to achieve better performance. The simulations demonstrate that these characters of the proposed approach enable it to fully enhance the content in images, to efficiently alleviate the enhancement of noise and to achieve much better enhancement effect than the traditional approaches. Key words wavelet transform - image contrast enhancement - multiscale analysis CLC number TP 391 Foundation item: Supported by the National Natural Science Foundation of China (69931010)Biography: Wu Ying-qian (1974-), male, Ph. D, research direction: image processing, image compression and wavelet.展开更多
A novel approach using shift invariant wavelet transform is presented for the contrast enhancement of radiographs. By exploiting cross-scale correlation among wavelet coefficients, edge information of radiographic ima...A novel approach using shift invariant wavelet transform is presented for the contrast enhancement of radiographs. By exploiting cross-scale correlation among wavelet coefficients, edge information of radiographic images is extracted and protected, while noise is smoothed out in the wavelet domain. Radiographs are then reconstructed from the transform coefficients modified at multi-scales by nonlinear enhancement operator. The method can achieve effectively contrast enhancement and edge-preserved denoising simultaneously, yet it is capable of giving visually distinct images and offering considerable benefits in medical diagnosis.展开更多
Processing and analyzing of medical images is one of the priority research areas. At the same time, the processing of images of cells occupies a special place. This is due to the fact that such studies allow for a com...Processing and analyzing of medical images is one of the priority research areas. At the same time, the processing of images of cells occupies a special place. This is due to the fact that such studies allow for a comprehensive diagnosis of the state of human health, identify and prevent the development of diseases in the early stages. We investigate the effectiveness of using wavelet analysis in color models, taking into account the preliminary change in the contrast of the input image. We consider the HSV color model and the image contrast modification procedure, which is based on the histogram change in the specified range with gamma correction. As a criterion for choosing parameters for changing the contrast of the image, we consider the entropy of the image. We also showed the advisability of using the value of the entropy index for the subsequent improvement of image analysis based on the wavelet ideology. We examined the general sequence of action for the analysis of image of megaloblastic anemia cells. This sequence is based on the choice of parameters for changing the contrast of the image and application of wavelet ideology.展开更多
文摘A novel wavelet-based algorithm for image enhancement is proposed in the paper. On the basis of multiscale analysis, the proposed algorithm solves efficiently the problem of noise over-enhancement, which commonly occurs in the traditional methods for contrast enhancement. The decomposed coefficients at same scales are processed by a nonlinear method, and the coefficients at different scales are enhanced in different degree. During the procedure, the method takes full advantage of the properties of Human visual system so as to achieve better performance. The simulations demonstrate that these characters of the proposed approach enable it to fully enhance the content in images, to efficiently alleviate the enhancement of noise and to achieve much better enhancement effect than the traditional approaches. Key words wavelet transform - image contrast enhancement - multiscale analysis CLC number TP 391 Foundation item: Supported by the National Natural Science Foundation of China (69931010)Biography: Wu Ying-qian (1974-), male, Ph. D, research direction: image processing, image compression and wavelet.
文摘A novel approach using shift invariant wavelet transform is presented for the contrast enhancement of radiographs. By exploiting cross-scale correlation among wavelet coefficients, edge information of radiographic images is extracted and protected, while noise is smoothed out in the wavelet domain. Radiographs are then reconstructed from the transform coefficients modified at multi-scales by nonlinear enhancement operator. The method can achieve effectively contrast enhancement and edge-preserved denoising simultaneously, yet it is capable of giving visually distinct images and offering considerable benefits in medical diagnosis.
文摘Processing and analyzing of medical images is one of the priority research areas. At the same time, the processing of images of cells occupies a special place. This is due to the fact that such studies allow for a comprehensive diagnosis of the state of human health, identify and prevent the development of diseases in the early stages. We investigate the effectiveness of using wavelet analysis in color models, taking into account the preliminary change in the contrast of the input image. We consider the HSV color model and the image contrast modification procedure, which is based on the histogram change in the specified range with gamma correction. As a criterion for choosing parameters for changing the contrast of the image, we consider the entropy of the image. We also showed the advisability of using the value of the entropy index for the subsequent improvement of image analysis based on the wavelet ideology. We examined the general sequence of action for the analysis of image of megaloblastic anemia cells. This sequence is based on the choice of parameters for changing the contrast of the image and application of wavelet ideology.
