Gradient based restoration of coal mine images obtained by underground wireless transmissions

Curvature-driven diffusion (CDD) principles were used to develop a novel gradient based image restoration algorithm.The algorithm fills in blocks of missing data in a wireless image after transmission through the network.When images are transmitted over fading channels,especially in the severe circumstances of a coal mine,blocks of the image may be destroyed by the effects of noise.Instead of using common retransmission query protocols the lost data is reconstructed by using the adaptive curvature-driven diffusion (ACDD) image restoration algorithm in the gradient domain of the destroyed image.Missing blocks are restored by the method in two steps:In step one,the missing blocks are filled in the gradient domain by the ACDD algorithm; in step two,and the image is reconstructed from the reformed gradients by solving a Poisson equation.The proposed method eliminates the staircase effect and accelerates the convergence rate.This is demonstrated by experimental results.