Abstract
Detail enhancement and noise reduction play crucial roles in high dynamic range infrared image processing. The main focuses are to compress the high dynamic range images with an effective way to display on lower dynamic range monitors, enhance the perceptibility of small details, and reduce the noises without causing artifacts. In this paper, we propose a new method for detail enhancement and noise reduction of high dynamic range infrared images. We first apply a guided image filter to smooth the input image and separate the image into the base component and the detail component. This process also gives us an adaptive weighting coefficient associated with the details generated by the filter kernel. After the filtering process, we compress the base component into the display range by our modified histogram projection and enhance the detail component using the gain mask of the filter weighting coefficient. At last, we recombine the two parts and quantize the result to 8-bit domain. Our method is significantly better than those based on histogram equalization (HE), and it also has better visual effect than bilateral filter-based methods. Furthermore, our proposed method is much faster, non-approximate and suffers much less gradient flipping artifacts compared to the bilateral filter-based methods because the guided image filter uses the local linear model. We demonstrate that our method is both effective and efficient in a great variety of applications. Experimental verification and detailed analysis are shown in this paper.
Published Version
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