Photoacoustic microscopy （PAM） is recognized as a powerful tool for various microcirculation system studies. To improve the spatial resolution for the PAM images, the requirements of the system will always be increa...Photoacoustic microscopy （PAM） is recognized as a powerful tool for various microcirculation system studies. To improve the spatial resolution for the PAM images, the requirements of the system will always be increased correspondingly. Without additional cost of the system, we address the problem of improving the resolution of PAM images by integrating a deconvolution model with a directional total variation regularization. Additionally, we present a primal-dual-based algorithm to solve the associated optimization problem efficiently. Results from both test images and some PAM images studies validate the effectiveness of the proposed method in enhancing the spatial resolution. We expect the proposed technique to be an alternative resolution enhancement tool for some important biomedical applications.展开更多
Microcirculation images often have low quality in acquisition process, which affect the following steps of process. This paper introduces enhancement algorithm based on nonsubsampled Contourlet transform (NSCT). It an...Microcirculation images often have low quality in acquisition process, which affect the following steps of process. This paper introduces enhancement algorithm based on nonsubsampled Contourlet transform (NSCT). It analyzes the characteristics of the microcirculation images generated, and separates microcirculation images to light weight and the reflection weight. It also analyzes the construction method on NSCT and proves that this method can be applied on microcirculation image enhancement algorithm. To correct light weight of microcirculation image and obtain enhancement image the enhancement microcirculation image was not only superior to the original image visually, but also improved objective data obviously. The algorithms provide a new method to microcirculation image pre-processing and guide the latter steps of the image processing.展开更多
基金supported by the National Natural Science Foundation of China(Nos.61174016,61201307,and 61371045)the Fundamental Research Funds for the Central Universities(No.2013132)
文摘Photoacoustic microscopy （PAM） is recognized as a powerful tool for various microcirculation system studies. To improve the spatial resolution for the PAM images, the requirements of the system will always be increased correspondingly. Without additional cost of the system, we address the problem of improving the resolution of PAM images by integrating a deconvolution model with a directional total variation regularization. Additionally, we present a primal-dual-based algorithm to solve the associated optimization problem efficiently. Results from both test images and some PAM images studies validate the effectiveness of the proposed method in enhancing the spatial resolution. We expect the proposed technique to be an alternative resolution enhancement tool for some important biomedical applications.
基金Doctoral Program of Higher Education of China grant number: 20093218110024+1 种基金International Science and Technology Cooperation Grantgrant number: BZ2008060
文摘Microcirculation images often have low quality in acquisition process, which affect the following steps of process. This paper introduces enhancement algorithm based on nonsubsampled Contourlet transform (NSCT). It analyzes the characteristics of the microcirculation images generated, and separates microcirculation images to light weight and the reflection weight. It also analyzes the construction method on NSCT and proves that this method can be applied on microcirculation image enhancement algorithm. To correct light weight of microcirculation image and obtain enhancement image the enhancement microcirculation image was not only superior to the original image visually, but also improved objective data obviously. The algorithms provide a new method to microcirculation image pre-processing and guide the latter steps of the image processing.
