Image visualization improvement based on gradient fusion
基于梯度域融合的图像视觉效果改善

There exists complementarity between different images of one scene. A better image can be obtained by fusing these images in gradient domain. The structure tensors of the images are fused and the local contrasts are incorporated in the design of fusion weights. The target gradient field whose structure tensor approximates the aforementioned tensor in the Frobenius norm sense is then obtained. An enhanced image is finally reconstructed from the target gradient field by least square fitting. Applications can include fusion of results by different enhancement methods, photos of the same scene with different focus or different exposures, etc. Experimental results demonstrate that the fused image can preserve significant details and structural information of each input image channel and the visual effect is improved.