BEEPS(bi-exponential edge-preserving filter) is used to enhance the details of infrared image in this paper. The original infrared image has a dynamic range of 12 or 14 bits, and the human observation range is only 8 bits. Usually, the original infrared image needs to be compressed and displayed by gray-scale remapped for displaying. For example, automatic gain control and histogram equalization are the most widely used image display technologies in infrared imaging systems, but they can lead to the loss of local details, and it is difficult to control the visibility of weak details in images. Therefore, an infrared image digital detail enhancement algorithm has emerged. Current digital enhancement algorithms can effectively enhance image details and avoid over-amplification of noise, but there are still some drawbacks, such as large computational load and poor application flexibility. Therefore, we use BEEPS in our algorithm to overcome these problems. This algorithm uses a two dimensional convolution to separate the detail information from an original infrared image, and turn the original image into the detail layer and the base layer. Detail layer processing is to transform two-dimensional convolution into one-dimensional convolution, and to complete one-dimensional convolution through iterative calculation. Then, the enhanced detail layer is added back to the base frequency layer of histogram equalization. This not only improves the computational efficiency, but also improves the visual quality of the original image. The BEEPS algorithm is proved to be excellent by image and data testing.
In this paper, we proposed a new infrared image detail enhancement approach. This approach could not only achieve the goal of enhancing the digital detail, but also make the processed image much closer to the real situation. Inspired by the joint-bilateral filter, two adjacent images were utilized to calculate the kernel functions in order to distinguish the detail information from the raw image. We also designed a new kernel function to modify the joint-bilateral filter and to eliminate the gradient reversal artifacts caused by the non-linear filtering. The new kernel is based on an adaptive emerge coefficient to realize the detail layer determination. The detail information was modified by the adaptive emerge coefficient along with two key parameters to realize the detail enhancement. Finally, we combined the processed detail layer with the base layer and rearrange the high dynamic image into monitor-suited low dynamic range to achieve better visual effect. Numerical calculation showed this new technology has the best value compare to the previous research in detail enhancement. Figures and data flowcharts were demonstrated in the paper.
In this paper, we propose an interframe phase-correlated registration scene-based nonuniformity correction technology. This technology is based on calculating the correlated phase information between two neighboring frames to determine the precise overlapping area of them. Usually, the common registration algorithms use the scene motion information to calculate the relative displacement of neighboring frames to determine the overlapping area. This approach may be interfered by the level of nonuniformity and cause the registration error. Furthermore, bring negative consequences to the correction process. Our technology effectively conquers this worry, and makes the level of nonuniformity careless during the registration process. We also adopt a new gain coefficient convergent method which proposed by our lasted study to finish the correction. The whole technology works with great performance. Detailed analysis, images and flow charts of this technology are also provided.