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. 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. 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. 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.