Medical image enhancement is an essential process for superior disease diagnosis as well as for detection of pathological lesion accurately. Computed Tomography (CT) is considered a vital medical imaging modality to e...Medical image enhancement is an essential process for superior disease diagnosis as well as for detection of pathological lesion accurately. Computed Tomography (CT) is considered a vital medical imaging modality to evaluate numerous diseases such as tumors and vascular lesions. However, speckle noise corrupts the CT images and makes the clinical data analysis ambiguous. Therefore, for accurate diagnosis, medical image enhancement is a must for noise removal and sharp/clear images. In this work, a medical image enhancement algorithm has been proposed using log transform in an optimization framework. In order to achieve optimization, a well-known meta-heuristic algorithm, namely: Cuckoo search (CS) algorithm is used to determine the optimal parameter settings for log transform. The performance of the proposed technique is studied on a low contrast CT image dataset. Besides this, the results clearly show that the CS based approach has superior convergence and fitness values compared to PSO as the CS converge faster that proves the efficacy of the CS based technique. Finally, Image Quality Analysis (IQA) justifies the robustness of the proposed enhancement technique.展开更多
It is desirable to develop new signal processing techniques for effectively extracting reflected waves under the strong interferences of borehole guided waves. We presented a multi-scale semblance method for the separ...It is desirable to develop new signal processing techniques for effectively extracting reflected waves under the strong interferences of borehole guided waves. We presented a multi-scale semblance method for the separation and velocity （slowness） analysis of the reflected waves and guided waves in borehole acoustic logging. It was specially designed for the newly developed tools with ultra-long source- receiver spacing for acoustic reflection survey. This new method was a combination of the dual tree com- plex wavelets transform （DT-CWT） and the slowness travel time coherence （STC） method. Applications to the 3D finite difference （FD） modeling simulated data and to the field array sonic waveform signals have demonstrated the ability of this method to appropriately extract the reflected waves under severe interference from the guided waves and to suppress noise in the time-frequency domain.展开更多
Based on the well-logging data of typical wells of Zhijin,Panxian and Weining areas in western Guizhou,the well-logging data GR of late Permian coal-bearing strata were processed and wavelet transform technique was us...Based on the well-logging data of typical wells of Zhijin,Panxian and Weining areas in western Guizhou,the well-logging data GR of late Permian coal-bearing strata were processed and wavelet transform technique was used to carry out the sequence stratigraphy division and correlation.The study mainly focuses on the controlling effects which Milankovitch had on high frequency sequence,Milankovitch cycle can be used as a ruler of sequence stratigraphy division and correlation to ensure the scientifcity and the unity of sequence stratigraphy division.According to well-logging signal of the ideal Milankovitch cycle,the corresponding relation between the wavelet scales and the cycles is determined by wavelet analysis.Through analyzing analog signals of subsequence sets to search the corresponding relation between various system tracts and the features of time-frequency,the internal features of wavelet transform scalogram could be made clearly.According to ideal model research,features of Milankovitch curves and wavelet spectrum can be seen clearly and each well can be classifed into four third-order sequences and two system tracts.At the same time Milankovitch cycle can realize the division and correlation of stratigraphic sequence in a quick and convenient way.展开更多
文摘Medical image enhancement is an essential process for superior disease diagnosis as well as for detection of pathological lesion accurately. Computed Tomography (CT) is considered a vital medical imaging modality to evaluate numerous diseases such as tumors and vascular lesions. However, speckle noise corrupts the CT images and makes the clinical data analysis ambiguous. Therefore, for accurate diagnosis, medical image enhancement is a must for noise removal and sharp/clear images. In this work, a medical image enhancement algorithm has been proposed using log transform in an optimization framework. In order to achieve optimization, a well-known meta-heuristic algorithm, namely: Cuckoo search (CS) algorithm is used to determine the optimal parameter settings for log transform. The performance of the proposed technique is studied on a low contrast CT image dataset. Besides this, the results clearly show that the CS based approach has superior convergence and fitness values compared to PSO as the CS converge faster that proves the efficacy of the CS based technique. Finally, Image Quality Analysis (IQA) justifies the robustness of the proposed enhancement technique.
基金National Natural Science Foundation of China (the project No.is 50674098)the National 863 Project of China (Grant 2006AA06Z207)theNational Basic Research Program of China (973 Program,2007CB209601).
文摘It is desirable to develop new signal processing techniques for effectively extracting reflected waves under the strong interferences of borehole guided waves. We presented a multi-scale semblance method for the separation and velocity （slowness） analysis of the reflected waves and guided waves in borehole acoustic logging. It was specially designed for the newly developed tools with ultra-long source- receiver spacing for acoustic reflection survey. This new method was a combination of the dual tree com- plex wavelets transform （DT-CWT） and the slowness travel time coherence （STC） method. Applications to the 3D finite difference （FD） modeling simulated data and to the field array sonic waveform signals have demonstrated the ability of this method to appropriately extract the reflected waves under severe interference from the guided waves and to suppress noise in the time-frequency domain.
基金supported by the National Natural Science Foundation of China (No. 41072076)the Youth Foundation of the National Natural Science Foundation of China (No. 41102100)
文摘Based on the well-logging data of typical wells of Zhijin,Panxian and Weining areas in western Guizhou,the well-logging data GR of late Permian coal-bearing strata were processed and wavelet transform technique was used to carry out the sequence stratigraphy division and correlation.The study mainly focuses on the controlling effects which Milankovitch had on high frequency sequence,Milankovitch cycle can be used as a ruler of sequence stratigraphy division and correlation to ensure the scientifcity and the unity of sequence stratigraphy division.According to well-logging signal of the ideal Milankovitch cycle,the corresponding relation between the wavelet scales and the cycles is determined by wavelet analysis.Through analyzing analog signals of subsequence sets to search the corresponding relation between various system tracts and the features of time-frequency,the internal features of wavelet transform scalogram could be made clearly.According to ideal model research,features of Milankovitch curves and wavelet spectrum can be seen clearly and each well can be classifed into four third-order sequences and two system tracts.At the same time Milankovitch cycle can realize the division and correlation of stratigraphic sequence in a quick and convenient way.
