Image Restoration Algorithm Based on Artificial Fish Swarm Micro Decomposition of Unknown Priori Pixel
Abstract: In this paper, we
put forward a new method to holographic reconstruct image that prior
information, module matching and edge structure information is unknown. The
proposed image holographic restoration algorithm combines artificial fish swarm
micro decomposition and brightness compensation. The traditional method uses
subspace feature information of multidimensional search method, it is failed to
achieve the fine structure information of image texture template matching and
the effect is not well. Therefore, it is difficult to holographic reconstruct
the unknown pixels. This weakness obstructs the application of image
restoration to many fields. Therefore, we builds a structure texture conduction
model for the priority determination of the block that to be repaired, then we
use subspace feature information multidimensional search method to the
confidence updates of unknown pixel. In order to maintain the continuity of
damaged region in image, the artificial fish swarm algorithm decomposition
model is combined with the image brightness compensation strategy of edge
feature. The simulation result shows that it has a good visual effect in image
restoration of a priori unknown pixel, recovery time and computation costs are
less, the stability and convergence performance is improved.
Author: Dan Sui, Fang He
Journal Code: jptkomputergg160213
