Focusing on the reconstruction artifact of photoacoustic images in restricted view, an improved fixed-point iterative quantitative photoacoustic imaging method was proposed. Firstly, the original photoacoustic pressure data detected by the detector were reconstructed by the traditional back projection reconstruction algorithm to obtain the original photoacoustic pressure image. Secondly, the original photoacoustic pressure image was filtered to remove the reconstruction artifact by adaptive Wiener filtering algorithm. Thirdly, the optical transmission model was used to solve the optical flux of the target imaging region. And finally, iterative calculation was performed to obtain the optical absorption coefficient of the target tissue. In addition, Toast++ software was introduced in the process of solving the optical flux to realize the forward solution of the optical transmission model, which improved the efficiency and accuracy of quantitative imaging. The phantom and in vivo experiments show that compared with the traditional fixed-point iterative method, the proposed method can obtain photoacoustic images with higher quality and there are fewer artifacts in the deep quantitative photoacoustic images reconstructed by the method. The optical absorption coefficient of the quantitatively reconstructed deep target tissue is very close to the optical absorption coefficient of the shallow target tissue, the former is about 70% of the latter. As a result, the quantitative reconstruction of the optical absorption coefficient of the deep biological tissue can be implemented by the proposed method.

The traditional road information extraction method is high-cost and slow-update. Compared with it, road or marine lane information extraction from crowdsourcing trajectory data is low-cost and easier to update. However, it is difficult to extract lane boundary due to vessel trajectory data with high noise, large data volume and uneven distribution across different regions. To solve this problem, an extraction method of marine lane boundary from exploiting trajectory big data was proposed. Firstly, the parallelized denoising, interpolation and trajectory segmentation for trajectory big data was conducted. Then, based on parallelization and Geohash-encoded spatial clustering, trajectory data was simplified into multiple square regions. The regions were divided and the NiBlack method was extended as SpatialNiBlack algorithm to recognize regions on lane. Finally, based on the filtering results, del-alpha-shape algorithm was proposed to construct a Delaunay triangulation network and obtain marine lane boundary. The theoretical analysis and experimental results show that the proposed method can achieve an accuracy of 86.7% and a recall rate of 79.4% when the maximum density value is 200, minimum density value is 10, length and width of window are 5 and 5 respectively. The experimental results show that the proposed method is effective to extract valuable marine lane boundaries from large-scale trajectory data.

Concerning the problem in pencil drawing generation that the pencil lines lack flexibility and textures lack directions, a method of combining directional textures and pencil sketches was proposed to produce pencil drawing from natural images. First, histogram matching was employed to obtain the tone map of the image, and an image was segmented into several regions according to color. For each region, tone and direction were computed by its color and its shape, to decide the final tone and direction of the pencil drawing. Then, an adjusted linear convolution was used to get the pencil sketches with certain randomness. Finally, the directional textures and sketches were combined to get the pencil drawing style. Different kinds of natural images could be converted to pencil drawings by the proposed method, and the renderings were compared with those of existing methods including line integral convolution and tone based method. The experimental results demonstrate that the directional texture can stimulate the manual pencil texture better and the adjusted sketches can mimic the randomness and flexibility of manual pencil drawings.

Focusing on the issue that the data acquisition amount of Photoacoustic Computed Tomography (PACT) based on ultrasonic array is generally huge, and the imaging process is time-consuming, a fast photoacoustic computed tomography method with Principal Component Analysis (PCA) was proposed to extend its applications to the field of hemodynamics. First, the matrix of image samples was constructed with part of full-sampling data. Second, the projection matrix representing the signal features could be derived by the decomposition of the sample matrix. Finally, the high-quality three-dimensional photoacoustic images could be recovered by this projection matrix under three-fold under-sampling. The experimental results on vivo back-vascular imaging of a rat show that, compared to the traditional back-projection method, the data acquisition amount of PACT using PCA can be decreased by about 35%, and the three-dimensional reconstruction speed is improved by about 40%. As a result, both the fast data acquisition and high-accurate image reconstruction are implemented successfully.

Concerning that the performance of Mobile Ad Hoc NETwork (MANET) with normal route method degrades obviously when being under attack in battlefield, a new STHR route strategy which integrating AODV（MANET route method） and Spay & Waiter protocols（DTN route method）to achieve high survivability was proposed in this paper. And to reduce the total network load, the method for choosing DTN nodes was designed. At the situation of hard network attacking, the target node may not be searched by AODV search extending ring. Then the zone covering nodes called ZCSEN in this paper would be used to start DTN route progress. In this way, the performance of MANET becomes stable even when it is under attack. The experimental results by 'ONE' show that the delivery rate of STHR is better than AODV and the delay time is shorter than Spay & Waiter route protocol.