Mammographic Feature Enhancement by Curvelet Transform

2011 ◽  
Vol 48-49 ◽  
pp. 664-667
Author(s):  
Qin Xue ◽  
Zhuang Zhi Yan ◽  
Sheng Qian Wang

This paper presents an approach for digital mammograms enhancement using curvelet transform. The curvelet transform breaks the limitation of the wavelet transform and provides efficient representation of smooth objects with discontinuities along curves. It has special micro-local features which make them especially adapted to the contrast enhancement of mammographic features. A kind of nonlinear enhancing function is applied to enhance the details of mammogram according to the importance of the curvelet coefficients from different scales and angles. Results show the technique is potential to improve the accuracy of cancer breast detection.

2011 ◽  
Vol 1 (3) ◽  
Author(s):  
T. Sumathi ◽  
M. Hemalatha

AbstractImage fusion is the method of combining relevant information from two or more images into a single image resulting in an image that is more informative than the initial inputs. Methods for fusion include discrete wavelet transform, Laplacian pyramid based transform, curvelet based transform etc. These methods demonstrate the best performance in spatial and spectral quality of the fused image compared to other spatial methods of fusion. In particular, wavelet transform has good time-frequency characteristics. However, this characteristic cannot be extended easily to two or more dimensions with separable wavelet experiencing limited directivity when spanning a one-dimensional wavelet. This paper introduces the second generation curvelet transform and uses it to fuse images together. This method is compared against the others previously described to show that useful information can be extracted from source and fused images resulting in the production of fused images which offer clear, detailed information.


2018 ◽  
Vol 14 (10) ◽  
pp. 1341-1350
Author(s):  
Ayush Dogra ◽  
Bhawna Goyal ◽  
Sunil Agrawal ◽  
Apoorav Maulik Sharma ◽  
Renu Vig

2003 ◽  
Vol 12 (6) ◽  
pp. 706-717 ◽  
Author(s):  
J.-L. Starck ◽  
F. Murtagh ◽  
E.J. Candes ◽  
D.L. Donoho

2017 ◽  
Vol 35 (3) ◽  
Author(s):  
Wagner Moreira Lupinacci ◽  
Anderson Peixoto de Franco ◽  
Fernando Vizeu Santos ◽  
Marco Antonio Cetale Santos

ABSTRACT. Time-frequency transforms are widely used in seismic exploration. These transforms enable analysis of the energy density of a non-stationary signal as functions of amplitude, time and frequency. The representation of energy density is not unique, and each transform has its advantages and disadvantages. The choice of which transform should be used depends on the application. In this paper, we propose a new way to analyze time-lapse anomalies using iso-frequency panels obtained by time-frequency transforms. We compared the iso-frequency panels of the Morlet Wavelet Transform and Choi-Williams Distribution. These panels revealed different characteristics and can provide additional information for the interpretation of time-lapse anomalies. We used seismic data from the Marimbá field of the Campos Basin, Brazil, for which base and monitor acquisitions were held in 1984 and 1999, respectively. We also used a special filtering approach to enhance seismic resolution and remove noise, whereby we applied the curvelet transform to remove noise, and employed a tool to correct the residual moveout and inverse Q filtering for attenuation correction. Then we analysed the time-lapse anomalies using iso-frequency panels. The main time-lapse anomalies appeared in the form of clouds in the iso-frequency panels obtained by the Morlet Wavelet Transform approach. Iso-frequency panels obtained by Choi-Williams Distribution showed a higher sensitivity and resolution for analyzing the anomalies. Our results show the great potential of these transforms for visualization of time-lapse anomalies. Keywords: time-lapse anomalies, spectrogram, Morlet Wavelet Transform, Choi-Williams Distribution. RESUMO. Transformadas tempo-frequência são amplamente utilizadas na exploração sísmica. Estas transformadas permitem a análise da densidade de energia de um sinal não-estacionário como funções de amplitude, tempo e frequência. A representação da densidade de energia de um sinal não é única, e cada transformada tem suas vantagens e desvantagens. A escolha da transformada que deve ser usada depende da aplicação. Neste artigo, propomos uma nova abordagem para analisar anomalias de dados time-lapse usando painéis iso-frequência obtidos através de transformadas tempo-frequência. Comparamos os painéis iso-frequência obtidos com a Transformada Wavelet de Morlet e a Distribuição de Choi-Williams. Estes painéis revelaram diferentes características que podem fornecer informações adicionais para a interpretação de anomalias time-lapse. Os dados sísmicos utilizados foram do Campo de Marimbá da Bacia de Campos, Brasil, os quais as aquisições base e monitor foram realizadas em 1984 e 1999, respectivamente. Antes da análise dos painéis iso-frequência, usamos um workflow para melhorar a resolução sísmica e a razão sinal-ruído. Neste workflow, aplicamos a Transformada Curvelet para remover ruídos aleatórios e coerentes, uma ferramenta para corrigir o moveout residual e um Q-filter para correção dos efeitos da atenuação. Após este workflow, as principais anomalias time-lapse apareceram na forma de nuvens nos painéis iso-frequência da Transformada Wavelet de Morlet. Já os painéis iso-frequência da Distribuição de Choi-Williams apresentaram uma maior sensibilidade e resolução para análise dessas anomalias. Os resultados mostraram o grande potencial dessas transformadas para a visualização e interpretação de anomalias time-lapse. Palavras-chave: anomalias time-lapse, espectrograma, Transformada Wavelet de Morlet, Distribuição Choi-Williams. 


2005 ◽  
Author(s):  
Changjiang Zhang ◽  
Xiaodong Wang ◽  
Jinshan Wang ◽  
Haoran Zhang

Sign in / Sign up

Export Citation Format

Share Document