Stripe noise removal for infrared image by minimizing difference between columns

• We analyze the reason that stripe noise commonly exists in infrared images.
• The observation model with stripe noise is described as linear model.
• The bias of column readout circuits are estimated by minimizing the difference between neighbor columns of images.
• The proposed approach can be carried out in a recursive way.

This paper introduces a novel approach to eliminate stripe noise in infrared images. The differences between bias voltages in column readout circuit of uncooled infrared sensors result in strong stripe noise which changes slowly in time. The problem can be solved by estimating the bias of each column of infrared images and correcting infrared images with the estimated biases. The bias estimation is translated into an energy optimization problem in the paper. The optimization aims to minimize difference between neighboring columns of images. Our approach can be processed on a single image, or in a recursive way in order to significantly reduce the computation in one frame time. Our approach is compared to the state-of-the-art the stripe noise removal method using realistic infrared images, and the experimental results show the effectiveness and efficiencies of our proposed approach.