图像场方向导数的局部区域重建

目的 目前图像修复的研究是以人眼不能察觉为目标,注重视觉效果而不追求重建的准确性。本文提出一种能准确重建图像缺损边缘的重建算法。方法 采用稳定场作为图像局部纹理的数学物理描述,提出基于点源影响函数的图像局部区域重建模型,该模型针对每一个缺损点,计算周围各已知点对它的影响,以期较为准确地重建该点;并根据该场中的方向导数,分析各已知点与缺损点的差异性及相似性,确定一种点源影响函数的计算方法,以实现该重建模型。结果 实验结果表明所提算法与传统修复算法相比,对图像边缘及纹理细节的重建更加清晰,同时保持了较好的整体视觉效果;且重建过程无迭代计算,具有较高的效率。结论 实验结果表明,该算法在重建效率和准确重建方面均取得了较好的成果。

Reconstructing image local regions based on directional derivative of a field

Objective A good visual effect has been the main target of present researchers in image reconstruction,and accurate local area reconstruction has been neglected. However,with the development of image analysis and recognition,more and more reconstructed images have been used for feature extraction. Therefore,accurate image reconstruction is arousing researchers' attention. At the same time,to achieve a higher reconstruction efficiency is also being taken seriously because of the real-time requirement and video processing. Pointing to the two problems above,a new algorithm is proposed in this paper. Method The stable field model is used to describe the image local region in this paper,a reconstructing model based on point-source influence function is proposed, and the directional derivative is used to analyze the calculation methods of the influence function. Given that it is the stable result of the interaction between the surface texture and structure of the object and light,a stationary image can be regarded as a stable energy field,so that we propose a stable field model of the image local region. In this model the missing pixel is the "point" and the known pixel is the "source". Then,a stable field equation of the image local region is set up according to the model. After the equation is solved,a new reconstruction model of the image local region based on the point-source influence function is proposed,which aims at reconstructing each missing pixel accurately by calculating the influence of the known pixels around. Finally,according to the directional derivative of the stable field,a method to calculate the point-source influence function is determined by analyzing both the similarities and differences between the missing pixel and the known,so that the reconstruction model could be achieved. Result In the reconstruction model,the missing pixels are assigned values one by one;before this,the influence function of each "source" around the "point" would be calculated first. Because both the calculation and the assignment to each missing pixel are as accurate as possible,compared with traditional reconstruction algorithms,the proposed algorithm achieves a better effect in accurate reconstruction. The proposed algorithm reconstructs damaged edges and texture more clearly than traditional ones and at the same time keeps a good visual effect. Moreover,because there are no iterative computations in the reconstruction process,the proposed algorithm has higher efficiency than traditional ones,which experimental results confirm that. Conclusion Based on the foundation of the image local region's stable field model,a new reconstruction model for the image local region is proposed,and it is achieved by calculating the point-source influence function with an algorithm based on the field directional derivative. Different from traditional ones,the proposed algorithm shifts the attention from the total visual effect to the reconstruction of each missing pixel,so that it achieves a more accurate reconstruction for damaged images. In addition, the lack of iterative computations makes it more efficient than traditional ones.