High dynamic range compression and detail enhancement of infrared images in the gradient domain

To find the trade-off between providing an accurate perception of the global scene and improving the visibility of details without excessively distorting radiometric infrared information, a novel gradient-domain-based visualization method for high dynamic range infrared images is proposed in this study. The proposed method adopts an energy function which includes a data constraint term and a gradient constraint term. In the data constraint term, the classical histogram projection method is used to perform the initial dynamic range compression to obtain the desired pixel values and preserve the global contrast. In the gradient constraint term, the moment matching method is adopted to obtain the normalized image; then a gradient gain factor function is designed to adjust the magnitudes of the normalized image gradients and obtain the desired gradient field. Lastly, the low dynamic range image is solved from the proposed energy function. The final image is obtained by linearly mapping the low dynamic range image to the 8-bit display range. The effectiveness and robustness of the proposed method are analyzed using the infrared images obtained from different operating conditions. Compared with other well-established methods, our method shows a significant performance in terms of dynamic range compression, while enhancing the details and avoiding the common artifacts, such as halo, gradient reversal, hazy or saturation.