Antcolony combined with adaptive threshold denoising and reconstruct for THz image

In this paper, an ant colony combined with adaptive threshold denoising algorithm for THz image is proposed. The ant colony is introduced to tackle the image edge detection problem; it is able to establish a pheromone matrix that represents the edge information presented at each pixel position of the image, according to the movements of a number of ants which are dispatched to move on the image. The adaptive threshold is derived in a Bayesian framework; it is adaptive to each subband because it depends on data-driven estimates of the parameters, and it is used to handle edge image and non-edge image which are obtained from ant colony. Experimental results are provided to show that the proposed approach outperforms several THz image denoising approaches developed in the traditional and literature.