Variational infrared image enhancement based on adaptive dual-threshold gradient field equalization

• Transforming the infrared image into its gradient domain to get the gradient histogram.
• The gradient field equalization with dual-threshold is obtained using the histogram equalization technique.
• Adopting the total variational model while constructing the objective function.
• Using the variational method, the enhanced image is reconstructed from the target gradient field.

Infrared images are characterized by low signal to noise ratio (SNR) and fuzzy texture edges. This article introduces the variational infrared image enhancement algorithm based on gradient field equalization with adaptive dual thresholds. Firstly, we transform the image into gradient domain and get the gradient histogram. Then, we do the gradient histogram equalization. By setting adaptive dual thresholds to qualify the gradients, the image is prevented from over enhancement. The total variation (TV) model is adopted in the reconstruction of the enhanced image to suppress noise. It is shown from experimental results that the image edge details are significantly enhanced, and therefore the algorithm is qualified for enhancement of infrared images in different applications.